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WO2025179204A1 - Motifs de déclenchement variable pour élimination de diaphonie - Google Patents

Motifs de déclenchement variable pour élimination de diaphonie

Info

Publication number
WO2025179204A1
WO2025179204A1 PCT/US2025/016889 US2025016889W WO2025179204A1 WO 2025179204 A1 WO2025179204 A1 WO 2025179204A1 US 2025016889 W US2025016889 W US 2025016889W WO 2025179204 A1 WO2025179204 A1 WO 2025179204A1
Authority
WO
WIPO (PCT)
Prior art keywords
laser
subset
detection data
laser emitters
sequence pattern
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/US2025/016889
Other languages
English (en)
Inventor
Jenny Wang
Peng WAN
Yang HAN
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
SGL Composites Inc
Original Assignee
SGL Composites Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by SGL Composites Inc filed Critical SGL Composites Inc
Publication of WO2025179204A1 publication Critical patent/WO2025179204A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06—Systems determining position data of a target
    • G01S17/08—Systems determining position data of a target for measuring distance only
    • G01S17/10—Systems determining position data of a target for measuring distance only using transmission of interrupted, pulse-modulated waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06—Systems determining position data of a target
    • G01S17/42—Simultaneous measurement of distance and other co-ordinates
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/50—Systems of measurement based on relative movement of target
    • G01S17/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/87—Combinations of systems using electromagnetic waves other than radio waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/481—Constructional features, e.g. arrangements of optical elements
    • G01S7/4814—Constructional features, e.g. arrangements of optical elements of transmitters alone
    • G01S7/4815—Constructional features, e.g. arrangements of optical elements of transmitters alone using multiple transmitters
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/481—Constructional features, e.g. arrangements of optical elements
    • G01S7/4817—Constructional features, e.g. arrangements of optical elements relating to scanning
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/481—Constructional features, e.g. arrangements of optical elements
    • G01S7/4818—Constructional features, e.g. arrangements of optical elements using optical fibres
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/483—Details of pulse systems
    • G01S7/484—Transmitters

Definitions

  • This disclosure relates generally to variable firing patterns of lasers in light detection and ranging (LiDAR) systems to remove crosstalk interference.
  • LiDAR Light detection and ranging
  • a LiDAR system may be a scanning or nonscanning system.
  • Some typical scanning LiDAR systems include a light source, a light transmitter, a light steering system, and a light detector.
  • the light source generates a light beam that is directed by the light steering system in particular directions when being transmitted from the LiDAR system.
  • a transmitted light beam is scattered or reflected by an object, a portion of the scattered or reflected light returns to the LiDAR system to form a return light pulse.
  • the light detector detects the return light pulse.
  • the LiDAR system can determine the distance to the object based on the speed of light. This technique of determining the distance is referred to as the time-of-flight (ToF) technique.
  • the light steering system can direct light beams along different paths to allow the LiDAR system to scan the surrounding environment and produce images or point clouds.
  • a typical nonscanning LiDAR system illuminates an entire field-of-view (FOV) rather than scanning through the FOV.
  • An example of the non-scanning LiDAR system is a flash LiDAR, which can also use the ToF technique to measure the distance to an object.
  • LiDAR systems can also use techniques other than time-of-flight and scanning to measure the surrounding environment.
  • LiDAR systems may handle a very large dynamic range of optical intensities from returned light. Retroreflectors may form return light having optical intensities that are many orders of magnitude greater than low reflectivity diffuse targets. To create high resolution point clouds at high frame rates (e.g., >10fps), multiple points in the scene may be sampled simultaneously. Crosstalk occurs when a high intensity signal returned from one part of the scene, e.g., from a retroreflector, is detected by a channel that is sampling another part of the scene, causing false positive detections. This crosstalk may be difficult to remove precisely, especially when the false positive signal is comparable to that of real targets. Thus, there is a continual need to improve LiDAR systems to identify and remove or prevent crosstalk.
  • a system for light ranging and detection may include a transmitter having a plurality of laser emitters configured to emit laser pulses toward a field of view, a scanner, a receiver comprising a plurality of photodetectors configured to detect return light from the field of view, and a controller.
  • the controller may be configured to control the plurality of laser emitters to emit laser pulses according to a first sequence pattern of a first plurality of subsets of the plurality of laser emitters in a first scan cycle.
  • the controller may be further configured to control the plurality of laser emitters to emit laser pulses according to a second sequence pattern of a second plurality of subsets of the plurality of laser emitters in a second scan cycle.
  • the second sequence pattern is different from the first sequence pattern and the second plurality of subsets is different from the first plurality of subsets.
  • FIG. 1 illustrates one or more example LiDAR systems disposed or included in a motor vehicle.
  • FIG. 2 is a block diagram illustrating interactions between an example LiDAR system and multiple other systems including a vehicle perception and planning system.
  • FIG. 3 is a block diagram illustrating an example LiDAR system.
  • FIG. 4A is a block diagram illustrating an example fiber-based laser source.
  • FIG. 4B is a block diagram illustrating an example semiconductor-based laser source.
  • FIGs. 5A-5C illustrate an example LiDAR system using pulse signals to measure distances to objects disposed in a field-of-view (FOV).
  • FOV field-of-view
  • FIG. 6 is a block diagram illustrating an example apparatus used to implement systems, apparatus, and methods in various embodiments.
  • FIGs. 7A-7B illustrate example transmitters that each includes an array of laser emitters that may be implemented in one or more LiDAR systems.
  • FIG. 8A illustrates an example subset grouping of laser emitters of the transmitter of FIG. 7 A.
  • FIGS. 8B-8C illustrate an example sequence pattern of the subset grouping of FIG. 8A.
  • FIG. 9A illustrates another example subset grouping of laser emitters of the transmitter of FIG. 7A.
  • FIGS. 9B-9C illustrate an example sequence pattern of the subset grouping of FIG. 9A.
  • FIG. 10A illustrates the same or similar sequence pattern as in FIGs. 8B-8C.
  • FIG. 10B illustrates the same or similar sequence pattern as in FIGs. 9B-9C.
  • FIG. IOC illustrates multiple sequence patterns in multiple scan cycles.
  • FIG. 11 illustrates a flowchart of an example method to operate a LiDAR system.
  • the term “or” is an inclusive “or” operator and is equivalent to the term “and/or,” unless the context clearly dictates otherwise.
  • the term “based on” is not exclusive and allows for being based on additional factors not described unless the context clearly dictates otherwise.
  • Coupled to is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms “coupled to” and “coupled with” are used synonymously. Within the context of a networked environment where two or more components or devices are able to exchange data, the terms “coupled to” and “coupled with” are also used to mean “communicatively coupled with”, possibly via one or more intermediary devices.
  • the components or devices can be optical, mechanical, and/or electrical devices.
  • first used to describe various elements
  • second used to describe various elements
  • these elements should not be limited by the terms. These terms are only used to distinguish one element from another.
  • a first laser emitter could be termed a second laser emitter and, similarly, a second laser emitter could be termed a first laser emitter, without departing from the scope of the various described examples.
  • the first laser emitter and the second laser emitter can both be laser emitters and, in some cases, can be separate and different laser emitters.
  • any language directed to a computer should be read to include any suitable combination of computing devices or network platforms, including servers, interfaces, systems, databases, agents, peers, engines, controllers, modules, or other types of computing devices operating individually or collectively.
  • the computing devices comprise a processor configured to execute software instructions stored on a tangible, non-transitory computer readable storage medium (e.g., hard drive, FPGA, PLA, solid state drive, RAM, flash, ROM, or any other volatile or nonvolatile storage devices).
  • the software instructions configure or program the computing device to provide the roles, responsibilities, or other functionality as discussed below with respect to the disclosed apparatus.
  • the disclosed technologies can be embodied as a computer program product that includes a non-transitory computer readable medium storing the software instructions that causes a processor to execute the disclosed steps associated with implementations of computer-based algorithms, processes, methods, or other instructions.
  • the various servers, systems, databases, or interfaces exchange data using standardized protocols or algorithms, possibly based on HTTP, HTTPS, AES, public-private key exchanges, web service APIs, known financial transaction protocols, or other electronic information exchanging methods.
  • Data exchanges among devices can be conducted over a packet-switched network, the Internet, LAN, WAN, VPN, or other type of packet switched network; a circuit switched network; cell switched network; or other type of network.
  • LiDAR systems may handle a very large dynamic range of optical intensities from returned light. Retroreflectors may form return light having optical intensities that are many orders of magnitude greater than low reflectivity diffuse targets. In order to create high resolution point clouds at high frame rates (e.g., > 1 Ofps), multiple points in the scene may be sampled simultaneously. Crosstalk occurs when a high intensity signal returned from one part of the scene, e.g., from a retroreflector, is detected by a channel that is sampling another part of the scene, causing false positive detections. This crosstalk may be difficult to remove precisely, especially when the false positive signal is comparable to that of real targets. Thus, there is a continual need to improve LiDAR systems to identify and remove or prevent crosstalk.
  • a system for light ranging and detection may include a transmitter having a plurality of laser emitters configured to emit laser pulses toward a field of view, a scanner, a receiver having a plurality of photodetectors configured to detect return light from the field of view, and a controller.
  • the controller may be configured to control the plurality of laser emitters to emit laser pulses according to a first sequence pattern of a first plurality of subsets of the plurality of laser emitters in a first scan cycle.
  • the controller may be configured to control the plurality of laser emitters to emit laser pulses according to a second sequence pattern of a second plurality of subsets of the plurality of laser emitters in a second scan cycle.
  • the second sequence pattern may different from the first sequence pattern and the second plurality of subsets may be different from the first plurality of subsets.
  • FIG. 1 illustrates one or more example LiDAR systems 110 and 120A-120I disposed or included in a motor vehicle 100.
  • Vehicle 100 can be a car, a sport utility vehicle (SUV), a truck, a train, a wagon, a bicycle, a motorcycle, a tricycle, a bus, a mobility scooter, a tram, a ship, a boat, an underwater vehicle, an airplane, a helicopter, an unmanned aviation vehicle (UAV), a spacecraft, etc.
  • Motor vehicle 100 can be a vehicle having any automated level.
  • motor vehicle 100 can be a partially automated vehicle, a highly automated vehicle, a fully automated vehicle, or a driverless vehicle.
  • a partially automated vehicle can perform some driving functions without a human driver’s intervention.
  • a partially automated vehicle can perform blind-spot monitoring, lane keeping and/or lane changing operations, automated emergency braking, smart cruising and/or traffic following, or the like. Certain operations of a partially automated vehicle may be limited to specific applications or driving scenarios (e.g., limited to only freeway driving).
  • a highly automated vehicle can generally perform all operations of a partially automated vehicle but with less limitations.
  • a highly automated vehicle can also detect its own limits in operating the vehicle and ask the driver to take over the control of the vehicle when necessary.
  • a fully automated vehicle can perform all vehicle operations without a driver’s intervention but can also detect its own limits and ask the driver to take over when necessary.
  • a driverless vehicle can operate on its own without any driver intervention.
  • motor vehicle 100 comprises one or more LiDAR systems 110 and 120A-120I.
  • LiDAR systems 110 and 120A-120I can be a scanning-based LiDAR system and/or a non-scanning LiDAR system (e.g., a flash LiDAR).
  • a scanning-based LiDAR system scans one or more light beams in one or more directions (e.g., horizontal and vertical directions) to detect objects in a field-of-view (FOV).
  • a non-scanning based LiDAR system transmits laser light to illuminate an FOV without scanning.
  • a flash LiDAR is a type of non-scanning based LiDAR system.
  • a flash LiDAR can transmit laser light to simultaneously illuminate an FOV using a single light pulse or light shot.
  • a LiDAR system is a frequently-used sensor of a vehicle that is at least partially automated.
  • motor vehicle 100 may include a single LiDAR system 110 (e.g., without LiDAR systems 120A-120I) disposed at the highest position of the vehicle (e.g., at the vehicle roof). Disposing LiDAR system 110 at the vehicle roof facilitates a 360-degree scanning around vehicle 100.
  • motor vehicle 100 can include multiple LiDAR systems, including two or more of systems 110 and/or 120A-120I. As shown in FIG. 1, in one embodiment, multiple LiDAR systems 110 and/or 120A-120I are attached to vehicle 100 at different locations of the vehicle.
  • LiDAR system 120A is attached to vehicle 100 at the front right corner; LiDAR system 120B is attached to vehicle 100 at the front center position; LiDAR system 120C is attached to vehicle 100 at the front left comer; LiDAR system 120D is attached to vehicle 100 at the right-side rear view mirror; LiDAR system 120E is attached to vehicle 100 at the left-side rear view mirror; LiDAR system 120F is attached to vehicle 100 at the back center position; LiDAR system 120G is attached to vehicle 100 at the back right corner; LiDAR system 120H is attached to vehicle 100 at the back left comer; and/or LiDAR system 1201 is attached to vehicle 100 at the center towards the backend (e.g., back end of the vehicle roof).
  • the backend e.g., back end of the vehicle roof
  • FIG. 2 is a block diagram 200 illustrating interactions between vehicle onboard LiDAR system(s) 210 and multiple other systems including a vehicle perception and planning system 220.
  • LiDAR system(s) 210 can be mounted on or integrated to a vehicle.
  • LiDAR system(s) 210 include sensor(s) that scan laser light to the surrounding environment to measure the distance, angle, and/or velocity of objects. Based on the scattered light that is returned to LiDAR system(s) 210, the LiDAR system(s) 210 can generate sensor data (e.g., image data or 3D point cloud data) representing the perceived external environment.
  • sensor data e.g., image data or 3D point cloud data
  • LiDAR system(s) 210 can include one or more of short-range LiDAR sensors, medium-range LiDAR sensors, and long-range LiDAR sensors.
  • a short-range LiDAR sensor measures objects located up to about 20-50 meters from the LiDAR sensor.
  • Short- range LiDAR sensors can be used for, e.g., monitoring nearby moving objects (e.g., pedestrians crossing street in a school zone), parking assistance applications, or the like.
  • a medium -range LiDAR sensor measures objects located up to about 70-200 meters from the LiDAR sensor.
  • Medium-range LiDAR sensors can be used for, e.g., monitoring road intersections, assistance for merging onto or leaving a freeway, or the like.
  • a long-range LiDAR sensor measures objects located up to about 200 meters and beyond.
  • Long-range LiDAR sensors are typically used when a vehicle is travelling at a high speed (e.g., on a freeway), such that the vehicle’s control systems may only have a few seconds (e.g., 6-8 seconds) to respond to any situations detected by the LiDAR sensor.
  • the LiDAR sensor data can be provided to vehicle perception and planning system 220 via a communication path 213 for further processing and controlling the vehicle operations.
  • Communication path 213 can be any wired or wireless communication links that can transfer data.
  • other vehicle onboard sensor(s) 230 are configured to provide additional sensor data separately or together with LiDAR system(s) 210.
  • Other vehicle onboard sensors 230 may include, for example, one or more camera(s) 232, one or more radar(s) 234, one or more ultrasonic sensor(s) 236, and/or other sensor(s) 238.
  • Camera(s) 232 can take images and/or videos of the external environment of a vehicle.
  • Camera(s) 232 can take, for example, high-definition (HD) videos having millions of pixels in each frame.
  • a camera includes image sensors that facilitate producing monochrome or color images and videos. Color information may be important in interpreting data for some situations (e.g., interpreting images of traffic lights).
  • Camera(s) 232 can include one or more of narrow-focus cameras, wider-focus cameras, side-facing cameras, infrared cameras, fisheye cameras, or the like.
  • the image and/or video data generated by camera(s) 232 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations.
  • Communication path 233 can be any wired or wireless communication links that can transfer data.
  • Camera(s) 232 can be mounted on, or integrated to, a vehicle at any location (e.g., rear-view mirrors, pillars, front grille, and/or back bumpers, etc.).
  • Other vehicle onboard sensor(s) 230 can also include radar sensor(s) 234.
  • Radar sensor(s) 234 use radio waves to determine the range, angle, and velocity of objects. Radar sensor(s) 234 produce electromagnetic waves in the radio or microwave spectrum. The electromagnetic waves reflect off an object and some of the reflected waves return to the radar sensor, thereby providing information about the object’s position and velocity.
  • Radar sensor(s) 234 can include one or more of short-range radar(s), medium-range radar(s), and long-range radar(s).
  • a short-range radar measures objects located at about 0.1-30 meters from the radar.
  • a short-range radar is useful in detecting objects located near the vehicle, such as other vehicles, buildings, walls, pedestrians, bicyclists, etc.
  • a short-range radar can be used to detect a blind spot, assist in lane changing, provide rear- end collision warning, assist in parking, provide emergency braking, or the like.
  • a medium-range radar measures objects located at about 30-80 meters from the radar.
  • a long-range radar measures objects located at about 80-200 meters.
  • Medium- and/or long- range radars can be useful in, for example, traffic following, adaptive cruise control, and/or highway automatic braking.
  • Sensor data generated by radar sensor(s) 234 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations.
  • Radar sensor(s) 234 can be mounted on, or integrated to, a vehicle at any location (e.g., rear-view mirrors, pillars, front grille, and/or back bumpers, etc.).
  • Other vehicle onboard sensor(s) 230 can also include ultrasonic sensor(s) 236.
  • Ultrasonic sensor(s) 236 use acoustic waves or pulses to measure objects located external to a vehicle. The acoustic waves generated by ultrasonic sensor(s) 236 are transmitted to the surrounding environment. At least some of the transmitted waves are reflected off an object and return to the ultrasonic sensor(s) 236. Based on the return signals, a distance of the object can be calculated.
  • Ultrasonic sensor(s) 236 can be useful in, for example, checking blind spots, identifying parking spaces, providing lane changing assistance into traffic, or the like.
  • Ultrasonic sensor(s) 236 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations.
  • Ultrasonic sensor(s) 236 can be mounted on, or integrated to, a vehicle at any location (e.g., rear-view mirrors, pillars, front grille, and/or back bumpers, etc.).
  • one or more other sensor(s) 238 may be attached in a vehicle and may also generate sensor data.
  • Other sensor(s) 238 may include, for example, global positioning systems (GPS), inertial measurement units (IMU), or the like.
  • Sensor data generated by other sensor(s) 238 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations.
  • communication path 233 may include one or more communication links to transfer data between the various sensor(s) 230 and vehicle perception and planning system 220.
  • sensor data from other vehicle onboard sensor(s) 230 can be provided to vehicle onboard LiDAR system(s) 210 via communication path 231.
  • LiDAR system(s) 210 may process the sensor data from other vehicle onboard sensor(s) 230.
  • sensor data from camera(s) 232, radar sensor(s) 234, ultrasonic sensor(s) 236, and/or other sensor(s) 238 may be correlated or fused with sensor data of LiDAR system(s) 210, thereby at least partially offloading the sensor fusion process performed by vehicle perception and planning system 220.
  • sensors onboard other vehicle(s) 250 are used to provide additional sensor data separately or together with LiDAR system(s) 210.
  • two or more nearby vehicles may have their own respective LiDAR sensor(s), camera(s), radar sensor(s), ultrasonic sensor(s), etc.
  • Nearby vehicles can communicate and share sensor data with one another. Communications between vehicles are also referred to as V2V (vehicle to vehicle) communications.
  • sensor data generated by other vehicle(s) 250 can be communicated to vehicle perception and planning system 220 and/or vehicle onboard LiDAR system(s) 210, via communication path 253 and/or communication path 251, respectively.
  • Communication paths 253 and 251 can be any wired or wireless communication links that can transfer data.
  • Sharing sensor data facilitates a better perception of the environment external to the vehicles. For instance, a first vehicle may not sense a pedestrian that is behind a second vehicle but is approaching the first vehicle. The second vehicle may share the sensor data related to this pedestrian with the first vehicle such that the first vehicle can have additional reaction time to avoid collision with the pedestrian.
  • data generated by sensors onboard other vehicle(s) 250 may be correlated or fused with sensor data generated by LiDAR system(s) 210 (or with other LiDAR systems located in other vehicles), thereby at least partially offloading the sensor fusion process performed by vehicle perception and planning system 220.
  • intelligent infrastructure system(s) 240 are used to provide sensor data separately or together with LiDAR system(s) 210. Certain infrastructures may be configured to communicate with a vehicle to convey information and vice versa. Communications between a vehicle and infrastructures are generally referred to as V2I (vehicle to infrastructure) communications.
  • intelligent infrastructure system(s) 240 may include an intelligent traffic light that can convey its status to an approaching vehicle in a message such as “changing to yellow in 5 seconds.”
  • Intelligent infrastructure system(s) 240 may also include its own LiDAR system mounted near an intersection such that it can convey traffic monitoring information to a vehicle. For example, a left-turning vehicle at an intersection may not have sufficient sensing capabilities because some of its own sensors may be blocked by traffic in the opposite direction.
  • sensors of intelligent infrastructure system(s) 240 can provide useful data to the left-turning vehicle.
  • data may include, for example, traffic conditions, information of objects in the direction the vehicle is turning to, traffic light status and predictions, or the like.
  • These sensor data generated by intelligent infrastructure system(s) 240 can be provided to vehicle perception and planning system 220 and/or vehicle onboard LiDAR system(s) 210, via communication paths 243 and/or 241, respectively.
  • Communication paths 243 and/or 241 can include any wired or wireless communication links that can transfer data.
  • sensor data from intelligent infrastructure system(s) 240 may be transmitted to LiDAR system(s) 210 and correlated or fused with sensor data generated by LiDAR system(s) 210, thereby at least partially offloading the sensor fusion process performed by vehicle perception and planning system 220.
  • V2V and V2I communications described above are examples of vehicle-to-X (V2X) communications, where the “X” represents any other devices, systems, sensors, infrastructure, or the like that can share data with a vehicle.
  • vehicle perception and planning system 220 receives sensor data from one or more of LiDAR system(s) 210, other vehicle onboard sensor(s) 230, other vehicle(s) 250, and/or intelligent infrastructure system(s) 240.
  • sensor fusion sub-system 222 can generate a 360-degree model using multiple images or videos captured by multiple cameras disposed at different positions of the vehicle.
  • Sensor fusion sub-system 222 obtains sensor data from different types of sensors and uses the combined data to perceive the environment more accurately.
  • a vehicle onboard camera 232 may not capture a clear image because it is facing the Sun or a light source (e.g., another vehicle’s headlight during nighttime) directly.
  • a LiDAR system 210 may not be affected as much and therefore sensor fusion sub-system 222 can combine sensor data provided by both camera 232 and LiDAR system 210, and use the sensor data provided by LiDAR system 210 to compensate the unclear image captured by camera 232.
  • a radar sensor 234 may work better than a camera 232 or a LiDAR system 210. Accordingly, sensor fusion sub-system 222 may use sensor data provided by the radar sensor 234 to compensate the sensor data provided by camera 232 or LiDAR system 210.
  • sensor data generated by other vehicle onboard sensor(s) 230 may have a lower resolution (e.g., radar sensor data) and thus may need to be correlated and confirmed by LiDAR system(s) 210, which usually has a higher resolution.
  • LiDAR system(s) 210 which usually has a higher resolution.
  • a sewage cover also referred to as a manhole cover
  • vehicle perception and planning system 220 may not be able to determine whether the object is an obstacle that the vehicle needs to avoid.
  • High- resolution sensor data generated by LiDAR system(s) 210 thus can be used to correlate and confirm that the object is a sewage cover and causes no harm to the vehicle.
  • Vehicle perception and planning system 220 further comprises an object classifier 223.
  • object classifier 223 can use any computer vision techniques to detect and classify the objects and estimate the positions of the objects.
  • object classifier 223 can use machine-learning based techniques to detect and classify objects. Examples of the machine-learning based techniques include utilizing algorithms such as region -based convolutional neural networks (R-CNN), Fast R-CNN, Faster R-CNN, histogram of oriented gradients (HOG), region-based fully convolutional network (R- FCN), single shot detector (SSD), spatial pyramid pooling (SPP-net), and/or You Only Look Once (Yolo).
  • R-CNN region -based convolutional neural networks
  • FCN region-based fully convolutional network
  • SSD single shot detector
  • SPP-net spatial pyramid pooling
  • Vehicle perception and planning system 220 further comprises a localization and vehicle posture sub-system 225.
  • localization and vehicle posture sub-system 225 can determine position of the vehicle and the vehicle’s posture. For example, using sensor data from LiDAR system(s) 210, camera(s) 232, and/or GPS data, localization and vehicle posture sub-system 225 can determine an accurate position of the vehicle on the road and the vehicle’s six degrees of freedom (e.g., whether the vehicle is moving forward or backward, up or down, and left or right).
  • high-definition (HD) maps are used for vehicle localization. HD maps can provide highly detailed, three-dimensional, computerized maps that pinpoint a vehicle’s location.
  • localization and vehicle posture subsystem 225 can determine precisely the vehicle’s current position (e.g., which lane of the road the vehicle is currently in, how close it is to a curb or a sidewalk) and predict vehicle’s future positions.
  • Vehicle perception and planning system 220 further comprises obstacle predictor 226.
  • Objects identified by object classifier 223 can be stationary (e.g., a light pole, a road sign) or dynamic (e.g., a moving pedestrian, bicycle, another car). For moving objects, predicting their moving path or future positions can be important to avoid collision.
  • Obstacle predictor 226 can predict an obstacle trajectory and/or warn the driver or the vehicle planning sub-system 228 about a potential collision. For example, if there is a high likelihood that the obstacle’s trajectory intersects with the vehicle’s current moving path, obstacle predictor 226 can generate such a warning.
  • Obstacle predictor 226 can use a variety of techniques for making such a prediction.
  • Such techniques include, for example, constant velocity or acceleration models, constant turn rate and velocity/accel eration models, Kalman Filter and Extended Kalman Filter based models, recurrent neural network (RNN) based models, long short-term memory (LSTM) neural network based models, encoder-decoder RNN models, or the like.
  • RNN recurrent neural network
  • LSTM long short-term memory
  • vehicle perception and planning system 220 further comprises vehicle planning sub-system 228.
  • Vehicle planning sub-system 228 can include one or more planners such as a route planner, a driving behaviors planner, and a motion planner.
  • the route planner can plan the route of a vehicle based on the vehicle’s current location data, target location data, traffic information, etc.
  • the driving behavior planner adjusts the timing and planned movement based on how other objects might move, using the obstacle prediction results provided by obstacle predictor 226.
  • the motion planner determines the specific operations the vehicle needs to follow.
  • the planning results are then communicated to vehicle control system 280 via vehicle interface 270.
  • the communication can be performed through communication paths 227 and 271, which include any wired or wireless communication links that can transfer data.
  • Vehicle control system 280 controls the vehicle’s steering mechanism, throttle, brake, etc., to operate the vehicle according to the planned route and movement.
  • vehicle perception and planning system 220 may further comprise a user interface 260, which provides a user (e.g., a driver) access to vehicle control system 280 to, for example, override or take over control of the vehicle when necessary.
  • User interface 260 may also be separate from vehicle perception and planning system 220.
  • User interface 260 can communicate with vehicle perception and planning system 220, for example, to obtain and display raw or fused sensor data, identified objects, vehicle’s location/posture, etc. These displayed data can help a user to better operate the vehicle.
  • User interface 260 can communicate with vehicle perception and planning system 220 and/or vehicle control system 280 via communication paths 221 and 261 respectively, which include any wired or wireless communication links that can transfer data. It is understood that the various systems, sensors, communication links, and interfaces in FIG. 2 can be configured in any desired manner and not limited to the configuration shown in FIG. 2.
  • FIG. 3 is a block diagram illustrating an example LiDAR system 300.
  • LiDAR system 300 can be used to implement LiDAR systems 110, 120A-120I, and/or 210 shown in FIGs. 1 and 2.
  • LiDAR system 300 comprises a light source 310, a transmitter 320, an optical receiver and light detector 330, a steering system 340, and control circuitry 350. These components are coupled together using communications paths 312, 314, 322, 332, 342, 352, 362, and 372. These communications paths include communication links (wired or wireless, bidirectional or unidirectional) among the various LiDAR system 300 components, but need not be physical components themselves.
  • the communications paths can be implemented by one or more electrical wires, buses, or optical fibers
  • the communication paths can also be wireless channels or free-space optical paths so that no physical communication medium is present.
  • communication path 314 between light source 310 and transmitter 320 may be implemented using one or more optical fibers.
  • Communication paths 332 and 352 may represent optical paths implemented using free space optical components and/or optical fibers.
  • communication paths 312, 322, 342, and 362 may be implemented using one or more electrical wires that carry electrical signals.
  • the communications paths can also include one or more of the above types of communication mediums (e.g., they can include an optical fiber and a free-space optical component, or include one or more optical fibers and one or more electrical wires).
  • LiDAR system 300 can be a coherent LiDAR system.
  • a coherent LiDAR system may include a route 372 providing a portion of transmission light from transmitter 320 to optical receiver and light detector 330.
  • Route 372 may include one or more optics (e.g., optical fibers, lens, mirrors, etc.) for providing the light from transmitter 320 to optical receiver and light detector 330.
  • the transmission light provided by transmitter 320 may be modulated light and can be split into two portions.
  • One portion is transmitted to the FOV, while the second portion is sent to the optical receiver and light detector 330 of the LiDAR system 300.
  • the second portion is also referred to as the light that is kept local (LO) to the LiDAR system 300.
  • the transmission light is scattered or reflected by various objects in the FOV and at least a portion of it forms return light.
  • the return light is subsequently detected and interferometrically recombined with the second portion of the transmission light that was kept local.
  • Coherent LiDAR provides a means of optically sensing an object’s range as well as its relative velocity along the line-of-sight (LOS).
  • LiDAR system 300 can also include other components not depicted in FIG. 3, such as power buses, power supplies, LED indicators, switches, etc. Additionally, other communication connections among components may be present, such as a direct connection between light source 310 and optical receiver and light detector 330 to provide a reference signal so that the time from when a light pulse is transmitted until a return light pulse is detected can be accurately measured.
  • Light source 310 outputs laser light for illuminating objects in a field of view (FOV).
  • the laser light can be infrared light having a wavelength in the range of 700 nm to 1mm.
  • Light source 310 can be, for example, a semiconductor-based laser (e.g., a diode laser) and/or a fiber-based laser.
  • a semiconductor-based laser can be, for example, an edge emitting laser (EEL), a vertical cavity surface emitting laser (VCSEL), an externalcavity diode laser, a vertical-external-cavity surface-emitting laser, a distributed feedback (DFB) laser, a distributed Bragg reflector (DBR) laser, an interband cascade laser, a quantum cascade laser, a quantum well laser, a double heterostructure laser, or the like.
  • EEL edge emitting laser
  • VCSEL vertical cavity surface emitting laser
  • DBR distributed Bragg reflector
  • a fiber-based laser is a laser in which the active gain medium is an optical fiber doped with rare-earth elements such as erbium, ytterbium, neodymium, dysprosium, praseodymium, thulium, and/or holmium.
  • a fiber laser is based on double-clad fibers, in which the gain medium forms the core of the fiber surrounded by two layers of cladding.
  • the double-clad fiber allows the core to be pumped with a high-power beam, thereby enabling the laser source to be a high power fiber laser source.
  • light source 310 comprises a master oscillator (also referred to as a seed laser) and power amplifier (MOP A).
  • the power amplifier amplifies the output power of the seed laser.
  • the power amplifier can be a fiber amplifier, a bulk amplifier, or a semiconductor optical amplifier.
  • the seed laser can be a diode laser (e.g., a Fabry-Perot cavity laser, a distributed feedback laser), a solid-state bulk laser, or a tunable externalcavity diode laser.
  • light source 310 can be an optically pumped microchip laser. Microchip lasers are alignment-free monolithic solid-state lasers where the laser crystal is directly contacted with the end mirrors of the laser resonator.
  • a microchip laser is typically pumped with a laser diode (directly or using a fiber) to obtain the desired output power.
  • a microchip laser can be based on neodymium-doped yttrium aluminum garnet (Y3AI5O12) laser crystals (i.e., Nd: YAG), or neodymium-doped vanadate (i.e., ND:YVO4) laser crystals.
  • light source 310 may have multiple amplification stages to achieve a high power gain such that the laser output can have high power, thereby enabling the LiDAR system to have a long scanning range.
  • the power amplifier of light source 310 can be controlled such that the power gain can be varied to achieve any desired laser output power.
  • FIG. 4A is a block diagram illustrating an example fiber-based laser source 400 having a seed laser and one or more pumps (e.g., laser diodes) for pumping desired output power.
  • Fiber-based laser source 400 is an example of light source 310 depicted in FIG. 3.
  • fiber-based laser source 400 comprises a seed laser 402 configured to generate initial light pulses of one or more wavelengths (e.g., infrared wavelengths such as 1550 nm), which are provided to a wavelength-division multiplexor (WDM) 404 via an optical fiber 403.
  • WDM wavelength-division multiplexor
  • Fiber-based laser source 400 further comprises a pump 406 for providing laser power (e.g., of a different wavelength, such as 980 nm) to WDM 404 via an optical fiber 405.
  • WDM 404 multiplexes the light pulses provided by seed laser 402 and the laser power provided by pump 406 onto a single optical fiber 407.
  • the output of WDM 404 can then be provided to one or more pre-amplifier(s) 408 via optical fiber 407.
  • Preamplifiers) 408 can be optical amplifier(s) that amplify optical signals (e.g., with about 10-30 dB gain). In some embodiments, pre-amplifier(s) 408 are low noise amplifiers.
  • Preamplifiers) 408 output to an optical combiner 410 via an optical fiber 409.
  • Combiner 410 combines the output laser light of pre-amplifier(s) 408 with the laser power provided by pump 412 via an optical fiber 411.
  • Combiner 410 can combine optical signals having the same wavelength or different wavelengths.
  • One example of a combiner is a WDM.
  • Combiner 410 provides combined optical signals to a booster amplifier 414, which produces output light pulses via optical fiber 415.
  • the booster amplifier 414 provides further amplification of the optical signals (e.g., another 20-40 dB).
  • the output light pulses can then be transmitted to transmitter 320 and/or steering mechanism 340 (shown in FIG. 3).
  • FIG. 4A illustrates one example configuration of fiber-based laser source 400.
  • Laser source 400 can have many other configurations using different combinations of one or more components shown in FIG. 4 A and/or other components not shown in FIG. 4A (e.g., other components such as power supplies, lens(es), filters, splitters, combiners, etc.).
  • fiber-based laser source 400 can be controlled (e.g., by control circuitry 350) to produce pulses of different amplitudes based on the fiber gain profile of the fiber used in fiber-based laser source 400.
  • Communication path 312 couples fiberbased laser source 400 to control circuitry 350 (shown in FIG. 3) so that components of fiber-based laser source 400 can be controlled by or otherwise communicate with control circuitry 350.
  • fiber-based laser source 400 may include its own dedicated controller. Instead of control circuitry 350 communicating directly with components of fiber-based laser source 400, a dedicated controller of fiber-based laser source 400 communicates with control circuitry 350 and controls and/or communicates with the components of fiber-based laser source 400.
  • Fiber-based laser source 400 can also include other components not shown, such as one or more power connectors, power supplies, and/or power lines.
  • FIG. 4B is a block diagram illustrating an example semiconductor-based laser source 440.
  • Semiconductor-based laser source 440 is an example of light source 310 depicted in FIG. 3.
  • laser source 440 is a Vertical -Cavity Surface-Emitting Laser (VCSEL), which is a type of semiconductor laser diode with a distinctive structure that allows it to emit light vertically from the surface of the chip, rather than through the edge of the chip like edge-emitting laser (EEL) diodes.
  • VCSELs have advantages like high-speed operation and easy integration into semiconductor devices.
  • FIG. 4B shows a cross-sectional view of an example VCSEL 440.
  • the VCSEL 440 includes a metal contact layer 442, an upper Bragg reflector 444, an active region 446, a lower Bragg reflector 448, a substrate 450, and another metal contact 452.
  • the metal contacts 442 and 452 are for making electrical contacts so that electrical current and/or voltage can be provided to VCSEL 440 for generating laser light.
  • the substrate layer 450 is a semiconductor substrate, which can be, for example, a gallium arsenide (GaAs) substrate.
  • VCSEL 440 uses a laser resonator, which includes two distributed Bragg reflector (DBR) reflectors (i.e., upper Bragg reflector 444 and lower Bragg reflector 448) with an active region 446 sandwiched between the DBR reflectors.
  • the active region 446 includes, for example, one or more quantum wells for the laser light generation.
  • the planar DBR-reflectors can be mirrors having layers with alternating high and low refractive indices. Each layer has a thickness of a quarter of the laser wavelength in the material, yielding intensity reflectivities above e.g., 99%.
  • High reflectivity mirrors in VCSELs can balance the short axial length of the gain region.
  • the upper and lower DBR reflectors 444 and 448 can be doped as p- type and n-type materials, forming a diode junction.
  • the p-type and n-type regions may be embedded between the reflectors, requiring a more complex semiconductor process to make electrical contact to the active region, but eliminating electrical power loss in the DBR structure.
  • the active region 446 is sandwiched between the DBR reflectors 444 and 448 of the VCSEL 440.
  • the active region is where the laser light generation occurs.
  • the active region 446 typically has a quantum well or quantum dot structure, which contains the gain medium responsible for light amplification.
  • VCSEL 440 When an electric current is applied to the active region 446, it generates photons by stimulated emission. The distance between the upper and lower DBR reflectors 444 and 448 defines the cavity length of the VCSEL 440. The cavity length in turn determines the wavelength of the emitted light and influences the laser's performance characteristics. When an electrical current is applied to the VCSEL 440, it generates light that bounces between the DBR reflectors 444 and 448 and exits the VCSEL 440 through, for example, the lower DBR reflector 448, producing a highly coherent and vertically emitted laser beam 454. VCSEL 440 can provide an improved beam quality, low threshold current, and the ability to produce single-mode or multi-mode output.
  • VCSEL 440 can be controlled (e.g., by control circuitry 350) to produce pulses of different amplitudes.
  • Communication path 312 couples VCSEL 440 to control circuitry 350 (shown in FIG. 3) so that components of VCSEL 440 can be controlled by or otherwise communicate with control circuitry 350.
  • VCSEL 440 may include its own dedicated controller. Instead of control circuitry 350 communicating directly with components of VCSEL 400, a dedicated controller of VCSEL 440 communicates with control circuitry 350 and controls and/or communicates with the components of VCSEL 440.
  • VCSEL 440 can also include other components not shown, such as one or more power connectors, power supplies, and/or power lines.
  • VCSEL 440 can be used to generate laser pulses or continuous wave (CW) lasers.
  • control circuitry 350 modulates the current supplied to the VCSEL 440. By rapidly turning the supply current on and off, pulses of laser light can be generated. The duration, repetition rate, and shape of the pulses can be controlled by adjusting the modulation parameters.
  • VCSEL 440 can also be a mode-locked VCSEL that uses a combination of current modulation and optical feedback to obtain ultra-short pulses. The mode-locked VCSEL may also be controlled to synchronize the phases of the laser modes to produce very short and high-intensity pulses.
  • VCSEL 440 can use Q-Switching techniques, which includes an optical switch in the laser cavity, temporarily blocking the lasing action and allows energy to build up in the cavity. When the switch is opened, a high-intensity pulse is emitted.
  • VCSEL 440 can also have external modulation performed by an external modulator (not shown), such as an electro-optic or acousto-optic modulator. The external modulation can be used in combination with the VCSEL itself to create pulsed output. The external modulator can be used to control the pulse duration and repetition rate.
  • the type of VCSEL used as at least a part of light source 310 depends on the application and the required pulse characteristics, such as pulse duration, repetition rate, and peak power.
  • typical operating wavelengths of light source 310 comprise, for example, about 850 nm, about 905 nm, about 940 nm, about 1064 nm, and about 1550 nm.
  • the upper limit of maximum usable laser power is set by the U.S. FDA (U.S. Food and Drug Administration) regulations.
  • the optical power limit at 1550 nm wavelength is much higher than those of the other aforementioned wavelengths. Further, at 1550 nm, the optical power loss in a fiber is low. These characteristics of the 1550 nm wavelength make it more beneficial for long-range LiDAR applications.
  • the amount of optical power output from light source 310 can be characterized by its peak power, average power, pulse energy, and/or the pulse energy density.
  • the peak power is the ratio of pulse energy to the width of the pulse (e.g., full width at half maximum or FWHM). Thus, a smaller pulse width can provide a larger peak power for a fixed amount of pulse energy.
  • a pulse width can be in the range of nanosecond or picosecond.
  • the average power is the product of the energy of the pulse and the pulse repetition rate (PRR). As described in more detail below, the PRR represents the frequency of the pulsed laser light. In general, the smaller the time interval between the pulses, the higher the PRR.
  • the PRR typically corresponds to the maximum range that a LiDAR system can measure.
  • Light source 310 can be configured to produce pulses at high PRR to meet the desired number of data points in a point cloud generated by the LiDAR system.
  • Light source 310 can also be configured to produce pulses at medium or low PRR to meet the desired maximum detection distance.
  • Wall plug efficiency (WPE) is another factor to evaluate the total power consumption, which may be a useful indicator in evaluating the laser efficiency.
  • WPE Wall plug efficiency
  • FIG. 1 multiple LiDAR systems may be attached to a vehicle, which may be an electrical-powered vehicle or a vehicle otherwise having limited fuel or battery power supply. Therefore, high WPE and intelligent ways to use laser power are often among the important considerations when selecting and configuring light source 310 and/or designing laser delivery systems for vehicle-mounted LiDAR applications.
  • Light source 310 can be configured to include many other types of light sources (e.g., laser diodes, short-cavity fiber lasers, solid-state lasers, and/or tunable external cavity diode lasers) that are configured to generate one or more light signals at various wavelengths.
  • light source 310 comprises amplifiers (e.g., preamplifiers and/or booster amplifiers), which can be a doped optical fiber amplifier, a solid- state bulk amplifier, and/or a semiconductor optical amplifier. The amplifiers are configured to receive and amplify light signals with desired gains.
  • LiDAR system 300 further comprises a transmitter 320.
  • Light source 310 provides laser light (e.g., in the form of a laser beam) to transmitter 320.
  • the laser light provided by light source 310 can be amplified laser light with a predetermined or controlled wavelength, pulse repetition rate, and/or power level.
  • Transmitter 320 receives the laser light from light source 310 and transmits the laser light to steering mechanism 340 with low divergence.
  • transmitter 320 can include, for example, optical components (e.g., lens, fibers, mirrors, etc.) for transmitting one or more laser beams to a field-of-view (FOV) directly or via steering mechanism 340. While FIG. 3 illustrates transmitter 320 and steering mechanism 340 as separate components, they may be combined or integrated as one system in some embodiments. Steering mechanism 340 is described in more detail below.
  • transmitter 320 often comprises a collimating lens or a lens group configured to collect the diverging laser beams and produce more parallel optical beams with reduced or minimum divergence.
  • the collimated optical beams can then be further directed through various optics such as mirrors and lens.
  • a collimating lens may be, for example, a single plano-convex lens or a lens group.
  • the collimating lens can be configured to achieve any desired properties such as the beam diameter, divergence, numerical aperture, focal length, or the like.
  • a beam propagation ratio or beam quality factor (also referred to as the M 2 factor) is used for measurement of laser beam quality.
  • the M 2 factor represents a degree of variation of a beam from an ideal Gaussian beam.
  • the M 2 factor reflects how well a collimated laser beam can be focused on a small spot, or how well a divergent laser beam can be collimated. Therefore, light source 310 and/or transmitter 320 can be configured to meet, for example, a scan resolution requirement while maintaining the desired M 2 factor.
  • One or more of the light beams provided by transmitter 320 are scanned by steering mechanism 340 to a FOV.
  • Steering mechanism 340 scans light beams in multiple dimensions (e.g., in both the horizontal and vertical dimension) to facilitate LiDAR system 300 to map the environment by generating a 3D point cloud.
  • a horizontal dimension can be a dimension that is parallel to the horizon or a surface associated with the LiDAR system or a vehicle (e.g., a road surface).
  • a vertical dimension is perpendicular to the horizontal dimension (i.e., the vertical dimension forms a 90-degree angle with the horizontal dimension).
  • Steering mechanism 340 will be described in more detail below.
  • the laser light scanned to an FOV may be scattered or reflected by an object in the FOV.
  • FIG. 3 further illustrates an optical receiver and light detector 330 configured to receive the return light.
  • Optical receiver and light detector 330 comprises an optical receiver that is configured to collect the return light from the FOV.
  • the optical receiver can include optics (e.g., lens, fibers, mirrors, etc.) for receiving, redirecting, focusing, amplifying, and/or filtering return light from the FOV.
  • the optical receiver often includes a collection lens (e.g., a single plano-convex lens or a lens group) to collect and/or focus the collected return light onto a light detector.
  • a light detector detects the return light focused by the optical receiver and generates current and/or voltage signals proportional to the incident intensity of the return light. Based on such current and/or voltage signals, the depth information of the object in the FOV can be derived.
  • One example method for deriving such depth information is based on the direct TOF (time of flight), which is described in more detail below.
  • a light detector may be characterized by its detection sensitivity, quantum efficiency, detector bandwidth, linearity, signal to noise ratio (SNR), overload resistance, interference immunity, etc.
  • SNR signal to noise ratio
  • the light detector can be configured or customized to have any desired characteristics.
  • optical receiver and light detector 330 can be configured such that the light detector has a large dynamic range while having a good linearity.
  • the light detector linearity indicates the detector’s capability of maintaining linear relationship between input optical signal power and the detector’s output.
  • a detector having good linearity can maintain a linear relationship over a large dynamic input optical signal range.
  • a light detector structure can be a PIN based structure, which has an undoped intrinsic semiconductor region (i.e., an “i” region) between a p-type semiconductor and an n-type semiconductor region.
  • Other light detector structures comprise, for example, an APD (avalanche photodiode) based structure, a PMT (photomultiplier tube) based structure, a SiPM (Silicon photomultiplier) based structure, a SPAD (single-photon avalanche diode) based structure, and/or quantum wires.
  • Si, InGaAs, and/or Si/Ge based materials can be used. It is understood that many other detector structures and/or material systems can be used in optical receiver and light detector 330.
  • a light detector may have an internal gain such that the input signal is amplified when generating an output signal.
  • noise may also be amplified due to the light detector’s internal gain.
  • Common types of noise include signal shot noise, dark current shot noise, thermal noise, and amplifier noise.
  • optical receiver and light detector 330 may include a pre-amplifier that is a low noise amplifier (LNA).
  • the pre-amplifier may also include a transimpedance amplifier (TIA), which converts a current signal to a voltage signal.
  • TIA transimpedance amplifier
  • NEP input equivalent noise or noise equivalent power
  • the NEP of a light detector specifies the power of the weakest signal that can be detected and therefore it in turn specifies the maximum range of a LiDAR system.
  • various light detector optimization techniques can be used to meet the requirement of LiDAR system 300. Such optimization techniques may include selecting different detector structures, materials, and/or implementing signal processing techniques (e.g., filtering, noise reduction, amplification, or the like).
  • signal processing techniques e.g., filtering, noise reduction, amplification, or the like.
  • coherent detection can also be used for a light detector.
  • Coherent detection allows for detecting amplitude and phase information of the received light by interfering the received light with a local oscillator. Coherent detection can improve detection sensitivity and noise immunity.
  • FIG. 3 further illustrates that LiDAR system 300 comprises steering mechanism 340.
  • steering mechanism 340 directs light beams from transmitter 320 to scan an FOV in multiple dimensions.
  • a steering mechanism is also referred to as a raster mechanism, a scanning mechanism, or simply a light scanner. Scanning light beams in multiple directions (e.g., in both the horizontal and vertical directions) facilitates a LiDAR system to map the environment by generating an image or a 3D point cloud.
  • a steering mechanism can be based on mechanical scanning and/or solid-state scanning. Mechanical scanning uses rotating mirrors to steer the laser beam or physically rotate the LiDAR transmitter and receiver (collectively referred to as transceiver) to scan the laser beam.
  • Solid-state scanning directs the laser beam to various positions through the FOV without mechanically moving any macroscopic components such as the transceiver.
  • Solidstate scanning mechanisms include, for example, optical phased arrays based steering and flash LiDAR based steering. In some embodiments, because solid-state scanning mechanisms do not physically move macroscopic components, the steering performed by a solid-state scanning mechanism may be referred to as effective steering.
  • a LiDAR system using solid-state scanning may also be referred to as a non-mechanical scanning or simply non-scanning LiDAR system (a flash LiDAR system is an example non-scanning LiDAR system).
  • Steering mechanism 340 can be used with a transceiver (e.g., transmitter 320 and optical receiver and light detector 330) to scan the FOV for generating an image or a 3D point cloud.
  • a transceiver e.g., transmitter 320 and optical receiver and light detector 330
  • a two-dimensional mechanical scanner can be used with a single-point or several single-point transceivers.
  • a single-point transceiver transmits a single light beam or a small number of light beams (e.g., 2-8 beams) to the steering mechanism.
  • a two-dimensional mechanical steering mechanism comprises, for example, polygon mirror(s), oscillating mirror(s), rotating prism(s), rotating tilt mirror surface(s), single-plane or multi-plane mirror(s), or a combination thereof.
  • steering mechanism 340 may include nonmechanical steering mechanism(s) such as solid-state steering mechanism(s).
  • steering mechanism 340 can be based on tuning wavelength of the laser light combined with refraction effect, and/or based on reconfigurable grating/phase array.
  • steering mechanism 340 can use a single scanning device to achieve two-dimensional scanning or multiple scanning devices combined to realize two- dimensional scanning.
  • a one-dimensional mechanical scanner can be used with an array or a large number of single-point transceivers.
  • the transceiver array can be mounted on a rotating platform to achieve 360-degree horizontal field of view.
  • a static transceiver array can be combined with the one-dimensional mechanical scanner.
  • a one-dimensional mechanical scanner comprises polygon mirror(s), oscillating mirror(s), rotating prism(s), rotating tilt mirror surface(s), or a combination thereof, for obtaining a forward-looking horizontal field of view. Steering mechanisms using mechanical scanners can provide robustness and reliability in high volume production for automotive applications.
  • a two-dimensional transceiver can be used to generate a scan image or a 3D point cloud directly.
  • a stitching or micro shift method can be used to improve the resolution of the scan image or the field of view being scanned.
  • signals generated at one direction e.g., the horizontal direction
  • signals generated at the other direction e.g., the vertical direction
  • steering mechanism 340 comprise one or more optical redirection elements (e.g., mirrors or lenses) that steer return light signals (e.g., by rotating, vibrating, or directing) along a receive path to direct the return light signals to optical receiver and light detector 330.
  • the optical redirection elements that direct light signals along the transmitting and receiving paths may be the same components (e.g., shared), separate components (e.g., dedicated), and/or a combination of shared and separate components. This means that in some cases the transmitting and receiving paths are different although they may partially overlap (or in some cases, substantially overlap or completely overlap).
  • LiDAR system 300 further comprises control circuitry 350.
  • Control circuitry 350 can be configured and/or programmed to control various parts of the LiDAR system 300 and/or to perform signal processing.
  • control circuitry 350 can be configured and/or programmed to perform one or more control operations including, for example, controlling light source 310 to obtain the desired laser pulse timing, the pulse repetition rate, and power; controlling steering mechanism 340 (e.g., controlling the speed, direction, and/or other parameters) to scan the FOV and maintain pixel registration and /or alignment; controlling optical receiver and light detector 330 (e.g., controlling the sensitivity, noise reduction, filtering, and/or other parameters) such that it is an optimal state; and monitoring overall system health/status for functional safety (e.g., monitoring the laser output power and/or the steering mechanism operating status for safety).
  • controlling light source 310 to obtain the desired laser pulse timing, the pulse repetition rate, and power
  • controlling steering mechanism 340 e.g., controlling the speed, direction, and/or other parameters
  • Control circuitry 350 can also be configured and/or programmed to perform signal processing to the raw data generated by optical receiver and light detector 330 to derive distance and reflectance information, and perform data packaging and communication to vehicle perception and planning system 220 (shown in FIG. 2). For example, control circuitry 350 determines the time it takes from transmitting a light pulse until a corresponding return light pulse is received; determines when a return light pulse is not received for a transmitted light pulse; determines the direction (e.g., horizontal and/or vertical information) for a transmitted/return light pulse; determines the estimated range in a particular direction; derives the reflectivity of an object in the FOV, and/or determines any other type of data relevant to LiDAR system 300.
  • direction e.g., horizontal and/or vertical information
  • LiDAR system 300 can be disposed in a vehicle, which may operate in many different environments including hot or cold weather, rough road conditions that may cause intense vibration, high or low humidities, dusty areas, etc. Therefore, in some embodiments, optical and/or electronic components of LiDAR system 300 (e.g., optics in transmitter 320, optical receiver and light detector 330, and steering mechanism 340) are disposed and/or configured in such a manner to maintain long term mechanical and optical stability. For example, components in LiDAR system 300 may be secured and sealed such that they can operate under all conditions a vehicle may encounter.
  • optical and/or electronic components of LiDAR system 300 e.g., optics in transmitter 320, optical receiver and light detector 330, and steering mechanism 340
  • components in LiDAR system 300 may be secured and sealed such that they can operate under all conditions a vehicle may encounter.
  • an anti-moisture coating and/or hermetic sealing may be applied to optical components of transmitter 320, optical receiver and light detector 330, and steering mechanism 340 (and other components that are susceptible to moisture).
  • housing(s), enclosure(s), fairing(s), and/or window can be used in LiDAR system 300 for providing desired characteristics such as hardness, ingress protection (IP) rating, self-cleaning capability, resistance to chemical and resistance to impact, or the like.
  • IP ingress protection
  • efficient and economical methodologies for assembling LiDAR system 300 may be used to meet the LiDAR operating requirements while keeping the cost low.
  • LiDAR system 300 can include other functional units, blocks, or segments, and can include variations or combinations of these above functional units, blocks, or segments.
  • LiDAR system 300 can also include other components not depicted in FIG. 3, such as power buses, power supplies, LED indicators, switches, etc.
  • other connections among components may be present, such as a direct connection between light source 310 and optical receiver and light detector 330 so that light detector 330 can accurately measure the time from when light source 310 transmits a light pulse until light detector 330 detects a return light pulse.
  • FIG. 5A e.g., illustrating a time-of-flight LiDAR system that uses light pulses
  • light pulse 502 when light pulse 502 reaches object 506, light pulse 502 scatters or reflects to form a return light pulse 508.
  • Return light pulse 508 may return to system 500 along light path 510.
  • the time from when transmitted light pulse 502 leaves LiDAR system 500 to when return light pulse 508 arrives back at LiDAR system 500 can be measured (e.g., by a processor or other electronics, such as control circuitry 350, within the LiDAR system).
  • This time-of-flight combined with the knowledge of the speed of light can be used to determine the range/di stance from LiDAR system 500 to the portion of object 506 where light pulse 502 scattered or reflected.
  • the external environment within the detectable range e.g., the field of view between path 504 and 532, inclusively
  • the external environment within the detectable range can be precisely mapped or plotted (e.g., by generating a 3D point cloud or images).
  • LiDAR system 500 may determine that there are no objects within a detectable range of LiDAR system 500 (e.g., an object is beyond the maximum scanning distance of LiDAR system 500). For example, in FIG. 5B, light pulse 526 may not have a corresponding return light pulse (as illustrated in FIG. 5C) because light pulse 526 may not produce a scattering event along its transmission path 528 within the predetermined detection range.
  • LiDAR system 500 or an external system in communication with LiDAR system 500 (e.g., a cloud system or service), can interpret the lack of return light pulse as no object being disposed along light path 528 within the detectable range of LiDAR system 500.
  • light pulses 502, 522, 526, and 530 can be transmitted in any order, serially, in parallel, or based on other timings with respect to each other.
  • FIG. 5B depicts transmitted light pulses as being directed in one dimension or one plane (e.g., the plane of the paper)
  • LiDAR system 500 can also direct transmitted light pulses along other dimension(s) or plane(s).
  • LiDAR system 500 can also direct transmitted light pulses in a dimension or plane that is perpendicular to the dimension or plane shown in FIG. 5B, thereby forming a 2-dimensional transmission of the light pulses.
  • This 2-dimensional transmission of the light pulses can be point-by-point, line-by-line, all at once, or in some other manner.
  • the density of a point cloud refers to the number of measurements (data points) per area performed by the LiDAR system.
  • a point cloud density relates to the LiDAR scanning resolution. Typically, a larger point cloud density, and therefore a higher resolution, is desired at least for the region of interest (ROI).
  • the density of points in a point cloud or image generated by a LiDAR system is equal to the number of pulses divided by the field of view. In some embodiments, the field of view can be fixed. Therefore, to increase the density of points generated by one set of transmission-receiving optics (or transceiver optics), the LiDAR system may need to generate a pulse more frequently. In other words, a light source in the LiDAR system may have a higher pulse repetition rate (PRR).
  • PRR pulse repetition rate
  • the farthest distance that the LiDAR system can detect may be limited. For example, if a return signal from a distant object is received after the system transmits the next pulse, the return signals may be detected in a different order than the order in which the corresponding signals are transmitted, thereby causing ambiguity if the system cannot correctly correlate the return signals with the transmitted signals.
  • the farthest distance the LiDAR system can detect may be 300 meters and 150 meters for 500 kHz and 1 MHz, respectively.
  • the density of points of a LiDAR system with 500 kHz repetition rate is half of that with 1 MHz.
  • Optical and/or signal processing techniques are also used to correlate between transmitted and return light signals.
  • Various systems, apparatus, and methods described herein may be implemented using digital circuitry, or using one or more computers using well-known computer processors, memory units, storage devices, computer software, and other components.
  • a computer includes a processor for executing instructions and one or more memories for storing instructions and data.
  • a computer may also include, or be coupled to, one or more mass storage devices, such as one or more magnetic disks, internal hard disks and removable disks, magneto-optical disks, optical disks, etc.
  • Various systems, apparatus, and methods described herein may be implemented using computers operating in a client-server relationship.
  • the client computers are located remotely from the server computers and interact via a network.
  • the client-server relationship may be defined and controlled by computer programs running on the respective client and server computers. Examples of client computers can include desktop computers, workstations, portable computers, cellular smartphones, tablets, or other types of computing devices.
  • client computers can include desktop computers, workstations, portable computers, cellular smartphones, tablets, or other types of computing devices.
  • Various systems, apparatus, and methods described herein may be implemented using a computer program product tangibly embodied in an information carrier, e.g., in a non-transitory machine-readable storage device, for execution by a programmable processor; and the method processes and steps described herein, including one or more of the steps of at least some of the FIGs.
  • a computer program is a set of computer program instructions that can be used, directly or indirectly, in a computer to perform a certain activity or bring about a certain result.
  • a computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.
  • Apparatus 600 comprises a processor 610 operatively coupled to a persistent storage device 620 and a main memory device 630.
  • Processor 610 controls the overall operation of apparatus 600 by executing computer program instructions that define such operations.
  • the computer program instructions may be stored in persistent storage device 620, or other computer- readable medium, and loaded into main memory device 630 when execution of the computer program instructions is desired.
  • processor 610 may be used to implement one or more components and systems described herein, such as control circuitry 350 (shown in FIG. 3), vehicle perception and planning system 220 (shown in FIG. 2), and vehicle control system 280 (shown in FIG. 2).
  • the method steps of at least some of FIGS. 1-9C can be defined by the computer program instructions stored in main memory device 630 and/or persistent storage device 620 and controlled by processor 610 executing the computer program instructions.
  • the computer program instructions can be implemented as computer executable code programmed by one skilled in the art to perform an algorithm defined by the method steps discussed herein in connection with at least some of FIGS. 1-9C.
  • the processor 610 executes an algorithm defined by the method steps of these aforementioned figures.
  • Apparatus 600 also includes one or more network interfaces 680 for communicating with other devices via a network.
  • Apparatus 600 may also include one or more input/output devices 690 that enable user interaction with apparatus 600 (e.g., display, keyboard, mouse, speakers, buttons, etc.).
  • Processor 610 may include both general and special purpose microprocessors and may be the sole processor or one of multiple processors of apparatus 600.
  • Processor 610 may comprise one or more central processing units (CPUs), and one or more graphics processing units (GPUs), which, for example, may work separately from and/or multi-task with one or more CPUs to accelerate processing, e.g., for various image processing applications described herein.
  • CPUs central processing units
  • GPUs graphics processing units
  • Processor 610, persistent storage device 620, and/or main memory device 630 may include, be supplemented by, or incorporated in, one or more application-specific integrated circuits (ASICs) and/or one or more field programmable gate arrays (FPGAs).
  • ASICs application-specific integrated circuits
  • FPGAs field programmable gate arrays
  • Input/output devices 690 may include peripherals, such as a printer, scanner, display screen, etc.
  • input/output devices 690 may include a display device such as a cathode ray tube (CRT), plasma or liquid crystal display (LCD) monitor for displaying information to a user, a keyboard, and a pointing device such as a mouse or a trackball by which the user can provide input to apparatus 600.
  • a display device such as a cathode ray tube (CRT), plasma or liquid crystal display (LCD) monitor for displaying information to a user, a keyboard, and a pointing device such as a mouse or a trackball by which the user can provide input to apparatus 600.
  • CTR cathode ray tube
  • LCD liquid crystal display
  • LiDAR system 300 may utilize one or more neural networks or other deep-learning techniques performed by processor 610 or other systems or apparatuses discussed herein.
  • FIG. 6 is a high-level representation of some of the components of such a computer for illustrative purposes.
  • FIGs. 7A-7B illustrate example transmitters 700A, 700B that each includes an array of laser emitters that may be implemented in one or more LiDAR systems such as those disclosed herein.
  • Each of the transmitters 700A, 700B is an example of the light source 310 and/or the transmitter 320 depicted in FIG. 3.
  • the transmitter 700A of FIG. 7A includes a 1 -dimensional array and the transmitter 700B of FIG. 7B includes a 2- dimensional array.
  • Other embodiments may include 1 -dimensional or 2-dimensional arrays with the same or different numbers of emitters or channels in the same or different arrangements as depicted in FIGs. 7A-7B.
  • the laser emitters of each transmitter 700A, 700B may be controllable individually and/or in subsets so that each transmitter 700A, 700B may be controlled to emit laser pulses in two or more sequence patterns of different subsets of the laser emitters.
  • a sequence patterns refers to an order in which subsets of emitters of the transmitters 700A, 700B are sequentially operated to emit laser pulses in subsets.
  • Each subset of laser emitters may be controlled such that all laser emitters in the subset emit laser pulses simultaneously for a given sequence pattern.
  • the subsets of a given sequence pattern may be different from the subsets of another sequence pattern to identify and eliminate ghost signals that may arise from cross-stalk.
  • the laser emitters may each be part of a channel that includes not only the given laser emitter, but also a corresponding photodiode of the receiver.
  • Each laser emitter within each of the arrays 700A, 700B is labeled with a channel number, e.g., channels 1-16 in the transmitter 700A of FIG. 7A and channels 1-32 in the transmitter 700B of FIG. 7B, to which the corresponding laser emitter belongs in this example.
  • a given laser emitter may emit a laser pulse into the FOV and then a portion of the laser pulse may reflect from an object in a propagation path of the laser pulse and return to the corresponding photodiode where the reflected laser pulse, or return light or signal, is detected.
  • a ghost signal is a signal that indicates the presence of an object in one of the channels that is not actually there.
  • Embodiments herein may identify and eliminate ghost signals by operating the laser emitters in different sequence patterns, each having different subsets of the laser emitters, in different sequential scan cycles. For example, suppose first and second laser emitters are grouped together in the same subset in a first sequence pattern but are grouped in different subsets in the second sequence pattern. Further suppose that an object that includes or functions as a retroreflector is in the propagation path of a first channel that includes the first laser emitter but a second channel that includes the second laser emitter is devoid of any objects.
  • the second channel may generate a ghost signal due to crosstalk from the retroreflector.
  • the second channel may not detect any return light.
  • each transmitter 700A, 700B may be grouped into any desired number and composition of subsets of two or more laser emitters per subset, each subset grouping being associated with one or more different sequence patterns.
  • the subset groupings may include one or more of the following.
  • One subset grouping may include a first subset that includes the odd-numbered laser emitters and a second subset that includes the even-numbered laser emitters.
  • Another subset grouping may include at least a first subset that includes one sequential portion of the laser emitters (e.g., laser emitters 1-8 for the transmitter 700A or laser emitters 1-16 for the transmitter 700B) and a second subset that includes a different second portion of the laser emitters (e.g., laser emitters 9-16 for the transmitter 700A or laser emitters 17-32 for the transmitter 700B).
  • a first subset that includes one sequential portion of the laser emitters (e.g., laser emitters 1-8 for the transmitter 700A or laser emitters 1-16 for the transmitter 700B)
  • a second subset that includes a different second portion of the laser emitters (e.g., laser emitters 9-16 for the transmitter 700A or laser emitters 17-32 for the transmitter 700B).
  • FIG. 8A illustrates another example subset grouping of laser emitters of the transmitter 700A of FIG. 7A, arranged in accordance with at least one embodiment herein.
  • the subset grouping of FIG. 8A includes a subset 802 of laser emitters that includes laser emitters 1-4, a subset 804 of laser emitters that includes laser emitters 5-8, a subset 806 of laser emitters that includes laser emitters 9-12, and a subset 808 of laser emitters that includes laser emitters 13-16.
  • the subsets 802, 804, 806, 808 of laser emitters may be fired, or controlled to emit laser pulses, in any desired sequence pattern in which one of the subsets 802, 804, 806, 808 is fired followed by each of the other subsets 802, 804, 806, 808 at different times.
  • a given subset emits laser pulses
  • all of the laser emitters in the given subset may emit laser pulses simultaneously.
  • FIGS. 8B-8C illustrate an example sequence pattern of the subset grouping of FIG. 8A, arranged in accordance with at least one embodiment herein.
  • the subset 802 (laser emitters 1-4) is fired first, followed by the subset 804 (laser emitters 5-8), followed by the subset 806 (laser emitters 9-12), followed by the subset 808 (laser emitters 13-16).
  • the subsets 802, 804, 806, 808 may be fired in a different order, such as in the reverse order (e.g., the subset 808, followed by the subset 806, followed by the subset 804, followed by the subset 802), or any other desired order.
  • the same sequence pattern may be repeated by the transmitter 700A in another scan cycle, as shown in FIG. 8C, or a different sequence pattern may follow (not illustrated in FIG. 8C).
  • the transmitter 700A may emit laser pulses simultaneously from the laser emitters 1-4 in the subset 802, then emit laser pulses simultaneously from the laser emitters 5-8 in the subset 804, then emit laser pulses simultaneously from the laser emitters 9-12 in the subset 806, then emit laser pulses simultaneously from the laser emitters 13-16 in the subset 808.
  • FIG. 9A illustrates another example subset grouping of laser emitters of the transmitter 700A of FIG. 7A, arranged in accordance with at least one embodiment herein.
  • the subset grouping of FIG. 9A includes a subset 902 of laser emitters that includes laser emitters 1, 5, 9, 13, a subset 904 of laser emitters that includes laser emitters 2, 6, 10, 14, a subset 906 of laser emitters that includes laser emitters 3, 7, 11, 15, and a subset 908 of laser emitters that includes laser emitters 4, 8, 12, 16.
  • the subsets 902, 904, 906, 908 of laser emitters may be fired in any desired sequence pattern in which one of the subsets 902, 904, 906, 908 is fired followed by each of the other subsets 902, 904, 906, 908 at different times.
  • a given subset emits laser pulses
  • all of the laser emitters in the given subset may emit laser pulses simultaneously.
  • FIGS. 9B-9C illustrate an example sequence pattern of the subset grouping of FIG. 9 A, arranged in accordance with at least one embodiment herein.
  • the subset 902 (laser emitters 1, 5, 9, 13) is fired first, followed by the subset 904 (laser emitters 2, 6, 10, 14), followed by the subset 906 (laser emitters 3, 7, 11, 15), followed by the subset 908 (laser emitters 4, 8, 12, 16).
  • the subsets 902, 904, 906, 908 may be fired in a different order, such as in the reverse order (e.g., the subset 908, followed by the subset 906, followed by the subset 904, followed by the subset 902), or any other desired order.
  • the same sequence pattern may be repeated by the transmitter 700A in another scan cycle, as shown in FIG. 9C, or a different sequence pattern may follow (not illustrated in FIG. 9C).
  • the transmitter 700A may emit laser pulses simultaneously from the laser emitters 1,
  • each sequence pattern may result in crosstalk false positives, or ghost signals, in certain receiver positions depending on how the subsets of laser emitters illuminate the scene but not others.
  • the sequence patterns may include more than one unique sequence patterns.
  • FIG. 10C illustrates the sequence pattern of FIG. 10A in a first scan cycle 1002 followed by the sequence pattern of FIG. 1 OB in a second scan cycle.
  • the two sequence patterns can be used to fire laser emitters in an alternating manner, e.g., alternating sequence patterns.
  • the sequence patterns may include more than one unique sequence patterns that are randomly generated.
  • sequence patterns may be pre-generated and programmed into the LiDAR system.
  • the more than one sequence patterns may include more than one unique sequence patterns that are generated based on data from return light detected by the receiver.
  • the sequence pattern may be generated based on LiDAR detection data from previous frames. Because there may be multiple frames in a short duration, sequence patterns may be generated for specific positions in a field of view to verify whether a previously detected point was crosstalk, particularly near positions of very high intensity of return light detected.
  • the laser emitters may emit laser pulses in the more than one sequence patterns by altematingly selecting from the more than one sequence patterns. As illustrated in FIG. 10C, the 2 different sequence patterns may be used one after the other, and then repeat the 2 different sequence patterns in this fashion.
  • the detected points at one position may help to verify whether the nearby detected points are crosstalk signals. As each of the different sequence patterns produces crosstalk in some channels but not others, the different sequence patterns complement each other’s filtering.
  • the laser emitters may emit laser pulses in the more than one sequence patterns by randomly selecting from the more than one sequence patterns.
  • a vehicle may include the LiDAR system of the above embodiments.
  • FIG. 11 illustrates a flowchart of an example method 1100 to operate a LiDAR system, arranged in accordance with at least one embodiment described herein.
  • the method 1100 may be performed and/or controlled by any suitable system, apparatus, or device.
  • any one or more of the LiDAR system 300, control circuitry 350, apparatus 600, processor 611, and/or other apparatus or devices herein may perform or direct performance of one or more of the operations associated with the method 1100.
  • the method 400 may be performed or controlled by one or more processors based on one or more computer-readable instructions stored on one or more non-transitory computer-readable media.
  • the method 1100 may include controlling multiple laser emitters of a transmitter to emit laser pulses toward a FOV according to a first sequence pattern of a first subset grouping, or a first grouping of subsets or a first plurality of subsets, of the laser emitters in a first scan cycle.
  • Block 1102 may be followed by block 1104.
  • the method 1100 may include controlling the laser emitters to emit laser pulses toward the FOV according to a second sequence pattern of a second subset grouping, or a second grouping of subsets or a second plurality of subsets, of the laser emitters in a second scan cycle.
  • the second sequence pattern is different from the first sequence pattern and the second grouping of subsets is different from the first grouping of subsets.
  • Block 1104 may be followed by block 1106.
  • the method 1100 may include receiving first detection data from multiple photodetectors based on the first scan cycle. For example, each of the photodetectors may generate a return signal in dependence on return light received at the photodetector during the first scan cycle. Block 1106 may be followed by block 1108.
  • the method 1100 may include receiving second detection data from the photodetectors based on the second scan cycle.
  • each of the photodetectors may generate a return signal in dependence on return light received at the photodetector during the second scan cycle.
  • the method 1100 further includes comparing the first detection data and the second detection data and identifying potential ghost signals based on inconsistencies between the first detection data and the second detection data.
  • controlling the laser emitters to emit laser pulses toward the FOV according to the first sequence pattern in the first scan cycle may include controlling a first subset of two or more of the laser emitters in the first scan cycle to emit laser pulses simultaneously from each laser emitter of the first subset.
  • Controlling the laser emitters to emit laser pulses toward the field of view according to the second sequence pattern in the second scan cycle may include controlling a second subset of two or more of the laser emitters in the second scan cycle to emit laser pulses simultaneously from each laser emitter of the second subset where the second subset is different from the first subset.
  • At least a first laser emitter may belong to both the first subset and the second subset.
  • At least a second laser emitter may belong to the first subset but not the second subset.
  • At least a third laser emitter may belong to the second subset but not the first subset.
  • cross-talk from the first laser emitter detected by photodetectors corresponding to the second and third laser emitters in a corresponding scan cycle may be detected and eliminated, reduced, ignored, or the like.
  • the method 1100 may further include controlling the laser emitters to emit laser pulses by alternating between the first sequence pattern and the second sequence pattern in successive scan cycles.
  • the first sequence pattern and the second sequence pattern may be two sequence patterns of a plurality of sequence patterns each associated with a different plurality of subsets of the plurality of laser emitters.
  • the method 1100 may further include controlling the laser emitters to emit laser pulses by randomly selecting a sequence pattern of the plurality of sequence patterns for each scan cycle.
  • the method 1100 may further include generating the second sequence pattern based on the first detection data. For example, if the first detection data indicates that multiple photodiodes corresponding to multiple laser emitters of the same subset in the first scan cycle all detected an object, the second sequence pattern may be generated to include subsets in which each of the laser emitters is in a different subset. By distributing the laser emitters across different subsets, any cross-talk from one of the laser emitters in the subset in the first scan cycle may be eliminated, or at least reduced, in the second sequence pattern since the laser emitters may be distributed across different subsets.
  • the method 1100 may further include removing the identified potential ghost signals from at least one of the first detection data or the second detection data to generate cleaned detection data.
  • the first plurality of subsets may include a first subset that includes at least a first laser emitter and a second laser emitter.
  • the second plurality of subsets may include a second subset that includes at least the second laser emitter and a third laser emitter.
  • Receiving the first detection data from the plurality of photodetectors may include receiving at least some of the first detection data from a first photodetector and a second photodetector of the plurality of photodetectors.
  • Receiving the second detection data from the plurality of photodetectors may include receiving at least some of the second detection data from the second photodetector and a third photodetector of the plurality of photodetectors.
  • the method 1100 may further include comparing the first detection data and the second detection data to make a first determination that an object detected in the at least some of the first detection data by the second photodetector is not detected in the at least some of the second detection data by the second photodetector.
  • the method 1100 may further include, based at least on the first determination, making a second determination that the object detected in the at least some of the first detection data by the second photodetector is a ghost signal.
  • a light detection and ranging (LiDAR) system comprising: a transmitter comprising a plurality of laser emitters configured to emit laser pulses toward a field of view; a scanner; a receiver comprising a plurality of photodetectors configured to detect return light from the field of view; and a controller configured to: control the plurality of laser emitters to emit laser pulses according to a first sequence pattern of a first plurality of subsets of the plurality of laser emitters in a first scan cycle; and control the plurality of laser emitters to emit laser pulses according to a second sequence pattern of a second plurality of subsets of the plurality of laser emitters in a second scan cycle; wherein the second sequence pattern is different from the first sequence pattern and the second plurality of subsets is different from the first plurality of subsets.
  • LiDAR light detection and ranging
  • Example 2 The LiDAR system of Example 1, wherein the controller is further configured to: receive first detection data from the plurality of photodetectors based on the first scan cycle; receive second detection data from the plurality of photodetectors based on the second scan cycle; compare the first detection data and the second detection data; and identify potential ghost signals based on inconsistencies between the first detection data and the second detection data.
  • Example s The LiDAR system of any example herein, particularly of Example 2, wherein the controller is further configured to remove the identified potential ghost signals from at least one of the first detection data or the second detection data to generate cleaned detection data.
  • Example 4 The LiDAR system of any example herein, particularly any one of Examples 1-3, wherein: the first plurality of subsets comprises a first subset of two or more of the plurality of laser emitters that is controlled in the first scan cycle to emit laser pulses simultaneously from each laser emitter of the first subset; the second plurality of subsets comprises a second subset of two or more of the plurality of laser emitters that is controlled in the second scan cycle to emit laser pulses simultaneously from each laser emitter of the second subset; the second subset is different from the first subset; and at least a first laser emitter of the plurality of laser emitters belongs to both the first subset and the second subset; at least a second laser emitter of the plurality of laser emitters belongs to the first subset but not the second subset; and at least a third laser emitter of the plurality of laser emitters belongs to the second subset but not the first subset.
  • Example 6 The LiDAR system of any example herein, particularly any one of Examples 1-5, wherein the first sequence pattern and the second sequence pattern are two of a plurality of sequence patterns each associated with a different plurality of subsets of the plurality of laser emitters and the controller is further configured to control the plurality of laser emitters to emit laser pulses by randomly selecting a sequence pattern of the plurality of sequence patterns for each scan cycle.
  • Example 7 The LiDAR system of any example herein, particularly any one of Examples 1-6, wherein the controller is further configured to generate the second sequence pattern based on the first detection data.
  • Example 8 The LiDAR system of any example herein, particularly any one of Examples 1-7, wherein the plurality of laser emitters are arranged in a linear array.
  • Example 9 The LiDAR system of any example herein, particularly any one of Examples 1-8, wherein the plurality of laser emitters are arranged in a two-dimensional array.
  • Example 10 The LiDAR system of any example herein, particularly any one of Examples 1-9, wherein the plurality of photodetectors correspond to the plurality of laser emitters in a one-to-one configuration.
  • Example 11 A vehicle comprising the LiDAR system of any example herein, particularly any one of Examples 1-10.
  • Example 12 A method to operate a light detection and ranging (LiDAR) system, the method comprising: controlling a plurality of laser emitters to emit laser pulses toward a field of view according to a first sequence pattern of a first plurality of subsets of the plurality of laser emitters in a first scan cycle; controlling the plurality of laser emitters to emit laser pulses toward the field of view according to a second sequence pattern of a second plurality of subsets of the plurality of laser emitters in a second scan cycle, wherein the second sequence pattern is different from the first sequence pattern and the second plurality of subsets is different from the first plurality of subsets; receiving first detection data from a plurality of photodetectors based on the first scan cycle; and receiving second detection data from the plurality of photodetectors based on the second scan cycle.
  • LiDAR light detection and ranging
  • Example 13 The method of any example herein, particularly Examples 12, further comprising: comparing the first detection data and the second detection data; and identifying potential ghost signals based on inconsistencies between the first detection data and the second detection data.
  • Example 14 The method of any example herein, particularly any one of Examples 12- 13, wherein: controlling the plurality of laser emitters to emit laser pulses toward the field of view according to the first sequence pattern in the first scan cycle comprises controlling a first subset of two or more of the plurality of laser emitters in the first scan cycle to emit laser pulses simultaneously from each laser emitter of the first subset; controlling the plurality of laser emitters to emit laser pulses toward the field of view according to the second sequence pattern in the second scan cycle comprises controlling a second subset of two or more of the plurality of laser emitters in the second scan cycle to emit laser pulses simultaneously from each laser emitter of the second subset; the second subset is different from the first subset; at least a first laser emitter of the plurality of laser emitters belongs to both the first subset and the second subset; at least a second laser emitter of the plurality of laser emitters belongs to the first subset but not the second subset; and at least a third laser emitter of the plurality of laser emitters belongs to the second subset but
  • Example 15 The method of any example herein, particularly any one of Examples 12-
  • Example 16 The method of any example herein, particularly any one of Examples 12-
  • first sequence pattern and the second sequence pattern are two of a plurality of sequence patterns each associated with a different plurality of subsets of the plurality of laser emitters, the method further comprising controlling the plurality of laser emitters to emit laser pulses by randomly selecting a sequence pattern of the plurality of sequence patterns for each scan cycle.
  • Example 17 The method of any example herein, particularly any one of Examples 12-
  • Example 18 The method of any example herein, particularly any one of Examples 12-
  • Example 19 The method of any example herein, particularly any one of Examples 12-
  • the first plurality of subsets includes a first subset that includes at least a first laser emitter and a second laser emitter of the plurality of laser emitters;
  • the second plurality of subsets includes a second subset that includes at least the second laser emitter and a third laser emitter of the plurality of laser emitters;
  • receiving the first detection data from the plurality of photodetectors includes receiving at least some of the first detection data from a first photodetector and a second photodetector of the plurality of photodetectors;
  • receiving the second detection data from the plurality of photodetectors includes receiving at least some of the second detection data from the second photodetector and a third photodetector of the plurality of photodetectors;
  • the method further comprises: comparing the first detection data and the second detection data to make a first determination that an object detected in the at least some of the first detection data by the second photodetector is not detected in the at least some of the second detection data by the second photodete
  • Example 20 A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform or control performance of operations comprising: controlling a plurality of laser emitters to emit laser pulses toward a field of view according to a first sequence pattern of a first plurality of subsets of a plurality of laser emitters in a first scan cycle; controlling the plurality of laser emitters to emit laser pulses toward the field of view according to a second sequence pattern of a second plurality of subsets of the plurality of laser emitters in a second scan cycle, wherein the second sequence pattern is different from the first sequence pattern and the second plurality of subsets is different from the first plurality of subsets; receiving first detection data from a plurality of photodetectors based on the first scan cycle; and receiving second detection data from the plurality of photodetectors based on the second scan cycle.

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  • Radar, Positioning & Navigation (AREA)
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  • Electromagnetism (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
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Abstract

Dans un mode de réalisation, un système de détection et de télémétrie par la lumière (LiDAR) inclut un émetteur, un scanner, un récepteur et un dispositif de commande. L'émetteur inclut de multiples émetteurs laser conçus pour émettre des impulsions laser vers un champ de vision. Le récepteur inclut de multiples photodétecteurs conçus pour détecter la lumière de retour provenant du champ de vision. Le dispositif de commande est configuré pour commander les émetteurs laser pour émettre des impulsions laser selon un premier motif de séquence d'un premier groupe de sous-ensembles des émetteurs laser dans un premier cycle de balayage. Le dispositif de commande est configuré pour commander les émetteurs laser pour émettre des impulsions laser selon un second motif de séquence d'un second groupe de sous-ensembles des émetteurs laser dans un second cycle de balayage. Le second motif de séquence est différent du premier motif de séquence et le second groupe de sous-ensembles est différent du premier groupe de sous-ensembles.
PCT/US2025/016889 2024-02-23 2025-02-21 Motifs de déclenchement variable pour élimination de diaphonie Pending WO2025179204A1 (fr)

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US20220043153A1 (en) * 2020-08-05 2022-02-10 Envisics Ltd Light Detection and Ranging
US20230084560A1 (en) * 2021-09-12 2023-03-16 James Thomas O'Keeffe Distributed lidar with shared light emitter

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Publication number Priority date Publication date Assignee Title
US20190094345A1 (en) * 2017-09-25 2019-03-28 Leica Geosystems Ag Laser scanner
US20200041614A1 (en) * 2018-08-03 2020-02-06 OPSYS Tech Ltd. Distributed Modular Solid-State LIDAR System
US20210396845A1 (en) * 2018-09-19 2021-12-23 Waymo Llc Methods and Systems for Dithering Active Sensor Pulse Emissions
US20200284883A1 (en) * 2019-03-08 2020-09-10 Osram Gmbh Component for a lidar sensor system, lidar sensor system, lidar sensor device, method for a lidar sensor system and method for a lidar sensor device
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US20230084560A1 (en) * 2021-09-12 2023-03-16 James Thomas O'Keeffe Distributed lidar with shared light emitter

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