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WO2019095139A1 - 数据处理方法和设备 - Google Patents

数据处理方法和设备 Download PDF

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Publication number
WO2019095139A1
WO2019095139A1 PCT/CN2017/111082 CN2017111082W WO2019095139A1 WO 2019095139 A1 WO2019095139 A1 WO 2019095139A1 CN 2017111082 W CN2017111082 W CN 2017111082W WO 2019095139 A1 WO2019095139 A1 WO 2019095139A1
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WIPO (PCT)
Prior art keywords
data
posture data
time
drone
time posture
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Ceased
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PCT/CN2017/111082
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English (en)
French (fr)
Inventor
魏亮辉
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SZ DJI Technology Co Ltd
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SZ DJI Technology Co Ltd
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Priority to CN201780013416.9A priority Critical patent/CN108700887A/zh
Priority to PCT/CN2017/111082 priority patent/WO2019095139A1/zh
Publication of WO2019095139A1 publication Critical patent/WO2019095139A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16M—FRAMES, CASINGS OR BEDS OF ENGINES, MACHINES OR APPARATUS, NOT SPECIFIC TO ENGINES, MACHINES OR APPARATUS PROVIDED FOR ELSEWHERE; STANDS; SUPPORTS
    • F16M11/00—Stands or trestles as supports for apparatus or articles placed thereon ; Stands for scientific apparatus such as gravitational force meters
    • F16M11/02—Heads
    • F16M11/18—Heads with mechanism for moving the apparatus relatively to the stand
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16M—FRAMES, CASINGS OR BEDS OF ENGINES, MACHINES OR APPARATUS, NOT SPECIFIC TO ENGINES, MACHINES OR APPARATUS PROVIDED FOR ELSEWHERE; STANDS; SUPPORTS
    • F16M13/00—Other supports for positioning apparatus or articles; Means for steadying hand-held apparatus or articles
    • F16M13/04—Other supports for positioning apparatus or articles; Means for steadying hand-held apparatus or articles for supporting on, or holding steady relative to, a person, e.g. by chains, e.g. rifle butt or pistol grip supports, supports attached to the chest or head

Definitions

  • the present disclosure relates to the field of data communication technologies, and more particularly, to a data processing method and apparatus.
  • the technology of shooting with the gimbal has been widely used.
  • the posture change of the camera-carrying head in the drone can be remotely controlled by the posture change of the control device (such as the mobile terminal), thereby controlling the camera to shoot the desired scene.
  • FIG. 1 shows a schematic diagram of a user wearing a control device, which is a virtual reality glasses.
  • the control device is equipped with an inertial measurement unit, and acquires the attitude data of the inertial measurement unit at a certain frequency (for example, 50 Hz), and then converts it into its own attitude.
  • the pitch angle, the yaw angle, and the roll angle are usually used to represent the poses, which respectively correspond to the angles of rotation around the x, y, and z axes in the three-dimensional coordinate system, and the range is generally -180 to 180 degrees, as shown in FIG. Show.
  • the attitude of the PTZ and the posture of the IMU of the control device can be recorded as their respective initial postures. Thereafter, the control device periodically acquires its own IMU attitude (including pitch angle, yaw angle, and roll angle) with respect to the initial posture, and transmits the three relative angles to the gimbal end. After receiving the relative angles, the gimbal end moves to the corresponding pitch angle, yaw angle and roll angle relative to its initial attitude, thereby achieving the relative attitude of the gimbal (ie, the attitude change of the gimbal) and the relative position of the control device. The effect of the gesture (ie, the attitude change of the control device) is consistent.
  • the camera on the pan/tilt can be used for recording at the same time. If the IMU of the control device moves unevenly (or the amplitude changes rapidly), or if the IMU status of the control device is transmitted wirelessly to the PTZ, there will be a delay, which will cause the pan/tilt movement to be unsmooth, and the captured video will appear. Obviously stuck (not smooth).
  • the present disclosure proposes a technical solution for smoothing relative pose data of an IMU transmitted to a pan-tilt.
  • a data processing method for controlling a gimbal of a drone includes acquiring target posture data and first time posture data of the pan/tilt, and the first time posture data is current posture data of the pan/tilt.
  • the data processing method also includes calculating a change between the target pose data and the first moment pose data. If the change is greater than a certain threshold, the target pose data is smoothed to calculate the second moment pose data.
  • the drone performs a corresponding operation according to the second time posture data. For example, the drone can adjust the attitude of the head of the drone based on the second time posture data.
  • a control device for a drone includes a gesture acquisition unit configured to acquire target pose data.
  • the control device further includes a processor configured to acquire first time posture data, and calculate a change between the target posture data and the first time posture data, the first time posture data is current posture data of the pan/tilt, and if If the change is greater than a certain threshold, smoothing processing is performed on the target pose data to calculate the second moment pose data.
  • the drone can perform a corresponding operation according to the second time posture data, for example, adjusting the posture of the head of the drone.
  • a drone including a pan/tilt head, a communication unit, an attitude sensor, and a processor.
  • the communication unit is configured to acquire target pose data.
  • the attitude sensor is configured to acquire the first time posture data of the pan/tilt, and the first time posture data is current attitude data of the pan/tilt.
  • the processor is configured to calculate a change between the target pose data and the first time pose data, and if the change is greater than a certain threshold, perform a smoothing process on the target pose data to calculate the second moment pose data.
  • the processor is further configured to adjust the attitude of the pan/tilt based on the second time posture data.
  • a control system for a drone including the control device described above and a drone including a pan/tilt.
  • the drone is configured to adjust the attitude of the gimbal under the control of the control device.
  • a control system for a drone including the drone described above and a control device.
  • the control device is configured to control the drone.
  • a computer readable storage medium is provided, stored Computer program.
  • the computer program When the computer program is run by the at least one processor, causing the at least one processor to perform the following operations: acquiring target posture data and first time posture data, the first time posture data is current attitude data of the pan/tilt; calculating the target posture data and the A change between the pose data at a moment; if the change is greater than a certain threshold, the target pose data is smoothed to calculate the second moment pose data.
  • the attitude data of the inertial measurement unit in the control device can be uniformly reached to the pan/tilt, and the change of the attitude data in the amplitude is relatively flat. Thereby, the smooth movement of the gimbal is realized, and the effect of video shooting is ensured.
  • Figure 1 shows a schematic diagram of a user wearing a control device.
  • FIG. 2 is a flow chart showing a method in accordance with one embodiment of the present disclosure.
  • FIG. 3 is a block diagram showing a control device according to an embodiment of the present disclosure.
  • FIG. 4 is a block diagram showing a drone in accordance with one embodiment of the present disclosure.
  • FIG. 5 is a schematic diagram showing a control device and a drone according to an embodiment of the present disclosure.
  • FIG. 6 is a schematic diagram showing interaction of a control device and a gimbal end according to an embodiment of the present disclosure.
  • FIG. 7 is a block diagram showing a computer readable storage medium in accordance with one embodiment of the present disclosure.
  • the method can be The control device is executed to remotely control the drone.
  • the method can also be performed by the drone itself.
  • it can be performed by a PTZ controller in the drone or can be performed by other independent control units in the drone.
  • the drones described herein may include unmanned aerial vehicles, unmanned vehicles, unmanned vehicles, and the like.
  • target posture data and first time posture data of the pan/tilt are acquired.
  • target attitude data refers to current attitude data of an inertial measurement unit (IMU) of a control device, which may be represented, for example, by a set of pitch angles, yaw angles, and roll angles in a three-dimensional coordinate system.
  • first moment posture data refers to the current attitude data of the gimbal in the drone, which can be represented by another set of pitch angle, yaw angle, and roll angle in the same three-dimensional coordinate system. The head of the drone is adjusted from the first moment posture to the target posture within a certain time interval.
  • step S220 a change between the target posture data and the first time posture data is calculated. For example, if both the target pose data and the first moment pose data are represented by the pitch angle, the yaw angle, and the roll angle in the three-dimensional coordinate system, the difference between the two sets of angles can be calculated as the target pose data and the A change in attitude data between moments.
  • step S230 if the change calculated at step S220 is greater than a specific threshold, the target posture data is smoothed to calculate the second time posture data, so that the gimbal of the drone smoothly smoothly from the first time interval The momentary posture is adjusted to the target posture.
  • the "second time posture data” describes the posture data of the pan/tilt at the next time after the first time. The drone can perform the corresponding operation according to the second time posture data.
  • the reason for the smoothing process is that the movement of the control device is usually not uniform.
  • taking virtual reality glasses as a control device as an example.
  • the IMU posture data directly transmitted to the pan/tilt virtual reality glasses may be uneven. beat.
  • the jump is more obvious, and the movement of the gimbal will also be larger. Therefore, the video taken by the camera carried on the gimbal is not effective because the pan-tilt is large.
  • the present disclosure proposes that after the IMU posture data is collected on the control device, the current IMU posture data is not immediately sent to the cloud station end, but the intermediate approximation value can be calculated according to the previous pan/tilt attitude and the current IMU posture data. And send the approximate attitude data to the cloud platform.
  • attitude data of the IMU is described by taking the y-axis (yaw angle) in the three-dimensional coordinate system as an example.
  • y-axis yaw angle
  • Those skilled in the art will appreciate that the principles described herein are equally applicable to the calculation of attitude data in other directions, such as the number of poses for the x-axis (pitch angle) and z-axis (roll angle). According to the calculation.
  • the yaw angle sent to the pan/tilt last time is S1 (also referred to as the first moment attitude data)
  • the current yaw angle of the IMU of the control device is Y2 (also known as target pose data). It is first determined whether (Y2-S1) is greater than a certain threshold. If (Y2-S1) is greater than a certain threshold (indicating that the target attitude change of the gimbal is more severe), then calculate:
  • the factor is closer to 1, the faster the approach speed, the larger the jitter will be, but the delay will be smaller.
  • the factor is closer to 0, the slower the approach speed, the smaller the jitter, but the larger the delay.
  • the value of factor can be adjusted as needed. For example, an adjustment switch can be added to the menu option of the control device to adjust the size of the factor.
  • the calculation of the above formula (i.e., smoothing) can be performed one or more times, so that S2 is better approximated to Y2.
  • S2 represents the yaw angle currently to be sent to the gimbal end.
  • the "specific threshold” can be set according to the desired smoothness. For example, if you want less jitter (so that the pan/tilt shots are smoother), you can set the threshold to be larger; instead, if you want to more quickly reflect the current pose of the control device at the gimbal end, you can set the threshold. It is smaller.
  • S2 can also be calculated as follows:
  • the meaning of the above formula is: Since the target posture change of the gimbal is relatively flat, the current posture data of the IMU can be directly sent to the gimbal end without causing obvious jitter of the picture taken by the camera on the gimbal.
  • the smoothing process is performed a plurality of times (for example, the process of Equation 1 above is performed), so that S2 is continuously approached to Y2 until Y2-S1 is smaller than a certain threshold.
  • the principle is that the current posture data of the IMU is not immediately sent to the gimbal end, but the smoothed IMU posture data is transmitted.
  • a stepwise smoothing process as described below can also be employed.
  • the absolute value of the difference of the posture data is divided into N levels.
  • the upper limit of the i-th file is D(i)
  • the lower limit is D(i-1)
  • Each gear corresponds to a unit moving distance L(n).
  • the yaw angle in the IMU pose data as an example.
  • the yaw angle of the last IMU attitude data is Y1
  • the yaw angle sent to the pan/tilt last time is S1
  • the yaw angle of the IMU posture data of the current control device is Y2.
  • the yaw angle of the pose data currently to be sent to the gimbal is S2
  • the incremental data is determined based on the absolute value
  • the first time posture data S1 is added to the incremental data to obtain the second time posture data S2; conversely, if (Y2-S1) is less than zero, the first time posture is The data S1 is subtracted from the incremental data to obtain second time posture data S2.
  • incrementmental data herein may include a product of a scale factor factor and (Y2-S1) in the formula (1), which may be preset according to a threshold interval; or may include the formula 3 A value (L(n)) corresponding to a specific threshold, which can be preset by the user.
  • the wireless environment is dry. Due to disturbances, the data received by the cloud station may be delayed. If the gimbal end runs to the position required by the attitude data every time it receives the data, there may be a sudden and slow movement, which affects the shooting effect of the camera on the gimbal.
  • the present disclosure proposes that the gesture data received by the gimbal end can be buffered, and the buffered attitude data is sent to the gimbal at a fixed frequency, so that the attitude change of the gimbal is uniform.
  • the corresponding attitude data can be transmitted to the pan/tilt at the same frequency as the frequency of the acquired attitude data of the control device, so that the motion of the pan/tilt is also smoother.
  • a gesture data queue can be created on the control device side to buffer the gesture data.
  • a timer can be created on the control device side to control the transmission, so as to control the device to determine the frequency acquisition attitude data and send the attitude data to the cloud station.
  • the pose data is stored at the end of the queue.
  • a set of posture data is acquired from the queue head and sent to the cloud station to control the movement of the gimbal to a position corresponding to the transmitted IMU posture data.
  • an attitude data queue may also be created on the gimbal side to buffer the received gesture data.
  • the processed posture data is sent to the PTZ terminal and stored in the tail of the data queue.
  • the cloud station side can sequentially obtain the cached posture data from the head of the data queue, and control the position of the gimbal running to the posture data.
  • the data in the gesture data queue should not be too much, otherwise it may cause a relatively large delay.
  • part of the data eg, data of the queue header
  • the frequency of the timer for controlling transmission may be set to be higher than the data acquisition (acquisition) frequency of the control device side IMU.
  • the frequency of the timer for controlling transmission can be set to twice the acquisition (acquisition) frequency of the control device side IMU.
  • the posture change of the control device can be uniformly reached to the pan/tilt, and the change in the amplitude of the posture data is relatively flat. Thereby, the smooth movement of the gimbal is realized, and the effect of video shooting is ensured.
  • FIG. 3 is a block diagram showing a control device according to an embodiment of the present disclosure.
  • the control device 30 includes a gesture acquisition unit 310 and a processor 320.
  • the control device 30 may include virtual reality glasses, and the data acquisition unit 310 may include virtual reality glasses.
  • the inertial measurement unit IMU, the processor 320 can include a microprocessor in the virtual reality glasses.
  • the control device 30 can also take other various forms, such as a remote controller, a somatosensory device, etc., without being limited to the above examples.
  • the gesture acquisition unit 310 is configured to acquire target gesture data.
  • the processor 320 is configured to acquire the first time posture data and calculate a change between the target attitude data and the first time posture data. If the change is greater than a certain threshold, smoothing processing is performed on the target pose data to calculate the second moment pose data.
  • the "target attitude data” refers to the current attitude data of the inertial measurement unit (IMU) of the control device
  • first time posture data refers to the current attitude data of the pan/tilt in the drone.
  • they can all be represented by a set of pitch angles, yaw angles, and roll angles in a three-dimensional coordinate system.
  • the "second time posture data” describes the attitude data of the gimbal at the next moment after the first moment, which can also be represented by a set of pitch angle, yaw angle and roll angle in the three-dimensional coordinate system. .
  • the processor 320 may calculate the absolute value of the difference between the target posture data Y2 acquired by the posture acquiring unit 310 and the first time posture data S1. If the absolute value of the difference is greater than a certain threshold, the incremental data is calculated based on the difference, and the incremental data is added to the first time posture data to obtain second time posture data.
  • the delta data may include the product of the difference (Y2-S1) in Equation 1 above and the scale factor factor, which is greater than 0 and not greater than one.
  • the delta data may include a value L(n) corresponding to a particular threshold in Equation 4.
  • processor 320 may be further configured to approximate the second time posture data to the target posture data by performing the smoothing process one or more times.
  • processor 320 may be further configured to transmit the second moment gesture data at a fixed frequency.
  • control device 30 may also include a buffer (not shown in Figure 3).
  • a buffer (not shown in Figure 3).
  • the processor 320 may be configured to buffer the second time posture data in the buffer before transmitting the second time posture data.
  • the buffered attitude data can be transmitted to the pan/tilt at a fixed frequency (for example, the corresponding attitude data is transmitted at the same frequency as the frequency at which the control device acquires the attitude data), so that the attitude change of the pan/tilt is uniform.
  • the drone 40 includes a pan/tilt head 410, a communication unit 420, an attitude sensor 430, and a processor 440.
  • a camera can be carried on the pan/tilt 410 to capture a desired picture.
  • the communication unit 420 is configured to acquire target posture data.
  • the attitude sensor 430 is configured to acquire first time posture data of the pan/tilt.
  • the meanings of "target posture data” and “first moment posture data” are the same as above, and will not be repeated for the sake of brevity.
  • the processor 440 is configured to calculate a change between the target pose data and the first time pose data. If the change is greater than a certain threshold, smoothing processing is performed on the target pose data to calculate second moment pose data. Then, the processor 440 can adjust the posture of the pan-tilt 410 according to the calculated second-time posture data, so that the camera on the pan-tilt 410 can capture the picture more smoothly.
  • the processor 440 may be configured to calculate an absolute value of a difference between the target attitude data Y2 and the first time posture data S1. If the absolute value of the difference is greater than a certain threshold, the incremental data is calculated based on the difference, and the incremental data is added to the first time posture data to obtain second time posture data.
  • the delta data may include a product of the difference (Y2-S1) in Equation 1 above and a scale factor factor, which may be set corresponding to a specific threshold, the value of which is greater than 0 and not greater than 1.
  • the delta data may include a value L(n) corresponding to a particular threshold in Equation 4.
  • the processor 440 may be configured to perform the smoothing process one or more times to approximate the second time pose data to the target pose data.
  • processor 440 can be configured to transmit second time posture data at a fixed frequency.
  • the drone 40 may also include a buffer (not shown in Figure 4).
  • a buffer (not shown in Figure 4).
  • the data received by the cloud station may be delayed. If the gimbal end runs to the position required by the attitude data every time it receives the data, there may be a sudden and slow movement, which affects the shooting effect of the camera on the gimbal.
  • the processor 440 may be configured to buffer the second time posture data in the buffer before transmitting the second time posture data. In this way, the buffered attitude data can be transmitted at a fixed frequency (for example, the corresponding attitude data is transmitted at the same frequency as the frequency at which the control device acquires the attitude data), so that the attitude change of the pan/tilt is uniform.
  • the processor 440 is further configured to discard a portion of the cached second moment gesture data if the second moment gesture data buffered in the buffer reaches a predetermined number.
  • the processor 440 is further configured to: if the second time posture data buffered in the buffer reaches a predetermined number, send the second time posture data according to a transmission frequency higher than an acquisition frequency of the target posture data.
  • the transmission frequency may be N times the acquisition frequency, where N is an integer greater than or equal to 1.
  • the transmission frequency can be set to twice the acquisition frequency.
  • processor 440 can be implemented in a variety of ways.
  • processor 440 can include separate computing units and control units.
  • the computing unit is configured to calculate a change between the target pose data and the first time pose data, and perform a smoothing process on the target pose data to calculate the second moment pose data if the change is greater than a certain threshold.
  • the control unit is configured to adjust the attitude of the pan/tilt according to the second time posture data.
  • processor 440 can include a memory and a microprocessor.
  • the memory is configured to store instructions that, when executed by the microprocessor, cause the microprocessor to perform: calculating a change between the target pose data and the first time pose data; and if the change is greater than a particular threshold, then The target posture data performs smoothing processing to calculate second time posture data; and adjusts the posture of the gimbal according to the second time posture data.
  • FIG. 5 is a schematic diagram showing a control device and a drone according to an embodiment of the present disclosure.
  • the top half of Figure 5 shows a picture example of a drone. It can be seen that the drone includes a gimbal, and the pan/tilt can carry one or more cameras.
  • the lower part of Fig. 5 shows a control device with an inertial measurement unit IMU, namely virtual reality glasses. The user can wear the virtual reality glasses to control the flight of the drone.
  • the control device instructs the control device to transmit control commands and IMU posture data to the drone.
  • FIG. 6 is a schematic diagram showing interaction of a control device and a gimbal end according to an embodiment of the present disclosure. It should be noted that the smoothing process shown in FIG. 6 is implemented in the control device. However, according to the above description, those skilled in the art can understand that the smoothing process according to the present disclosure can also be implemented on the gimbal side, for example, in a pan/tilt controller.
  • the control device with the IMU periodically acquires the posture data of the IMU under the control of the timer. Then, the smoothing process described above is performed on the acquired posture data of the IMU to obtain the processed posture data.
  • the control device transmits the processed posture data (for example, in a wireless communication manner) to the cloud station.
  • the cloud station side stores the received IMU posture data into the IMU posture data queue, and periodically acquires the IMU posture data from the queue under the control of the timer. Then,
  • the pan/tilt controller can control the attitude of the gimbal itself according to the acquired IMU posture data.
  • Table 1 shows the sequence of commands sent to the PTZ with the existing technical solution:
  • Table 2 shows a sequence of commands sent to the PTZ in the case of employing the technical solution according to the present disclosure:
  • the IMU posture data transmitted to the gimbal end is more uniform in time, and the change is smoother in terms of spatial extent.
  • the movement of the gimbal is also smoother, so that the video captured by the camera carried on the gimbal is also smoother, reducing the change of the IMU too fast. Or the video jamming caused by uneven changes.
  • embodiments of the present disclosure may be implemented by means of a computer program product.
  • the computer program product can be a computer readable storage medium.
  • a computer program is stored on a computer readable storage medium, and when executed on a computing device, related operations can be performed to implement the above-described aspects of the present disclosure.
  • FIG. 7 is a block diagram showing a computer readable storage medium 70 in accordance with one embodiment of the present disclosure.
  • computer readable storage medium 70 includes a program 710.
  • the program 710 when executed by the at least one processor, causes the at least one processor to: acquire target pose data and first time pose data; calculate a change between the target pose data and the first moment pose data; if the change
  • the target posture data is smoothed to calculate the second moment posture data, so that the head of the drone is smoothly adjusted from the first moment posture to the target posture within a certain time interval.
  • the "second time posture data” describes the posture data at the next time after the first time.
  • Examples of computer readable storage media 70 in embodiments of the present disclosure include, but are not limited to, semiconductor storage media, optical storage media, magnetic storage media, or any other computer readable storage media.
  • Such an arrangement of the present disclosure is typically provided as software, code, and/or other data structures, such as one or more, that are arranged or encoded on a computer readable medium such as an optical medium (eg, CD-ROM), floppy disk, or hard disk.
  • a computer readable medium such as an optical medium (eg, CD-ROM), floppy disk, or hard disk.
  • Software or firmware or such a configuration may be installed on the computing device such that one or more processors in the computing device perform the technical solutions described in the embodiments of the present disclosure.
  • each functional module or individual feature of the device used in each of the above embodiments may be implemented or executed by circuitry, typically one or more integrated circuits.
  • Circuitry designed to perform the various functions described in this specification can include general purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs) or general purpose integrated circuits, field programmable gate arrays (FPGAs), or others. Programming logic, discrete gate or transistor logic, or discrete hardware Component, or any combination of the above.
  • a general purpose processor may be a microprocessor, or the processor may be an existing processor, controller, microcontroller, or state machine.
  • the above general purpose processor or each circuit may be configured by a digital circuit or may be configured by a logic circuit.
  • the present disclosure may also use integrated circuits obtained using the advanced technology.
  • the program running on the device may be a program that causes a computer to implement the functions of the embodiments of the present invention by controlling a central processing unit (CPU).
  • the program or information processed by the program may be temporarily stored in a volatile memory (such as a random access memory RAM), a hard disk drive (HDD), a non-volatile memory (such as a flash memory), or other memory system.
  • a program for realizing the functions of the embodiments of the present invention can be recorded on a computer readable recording medium.
  • the corresponding functions can be realized by causing a computer system to read programs recorded on the recording medium and execute the programs.
  • the so-called "computer system” herein may be a computer system embedded in the device, and may include an operating system or hardware (such as a peripheral device).

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  • Radar, Positioning & Navigation (AREA)
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  • General Engineering & Computer Science (AREA)
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Abstract

提供了一种数据处理方法，用于控制无人机的云台。该数据处理方法包括获取目标姿态数据和云台的第一时刻姿态数据。第一时刻姿态数据是云台的当前姿态数据。该数据处理方法还包括计算目标姿态数据与第一时刻姿态数据之间的变化。如果该变化大于特定阈值，则对目标姿态数据进行平滑处理，以计算第二时刻姿态数据。无人机根据第二时刻姿态数据平滑地调整云台的姿态。还提供了一种控制设备、一种无人机和一种计算机可读存储介质。

Description

数据处理方法和设备 技术领域
本公开涉及数据通信技术领域，更具体地，本公开涉及一种数据处理方法和设备。
背景技术
当前，利用云台进行拍摄的技术得到了广泛的应用。例如，在通过无人机进行航拍时，可以通过控制设备(诸如移动终端)的姿态变化来远程控制无人机中携带相机的云台的姿态变化，从而控制相机对期望的场景进行拍摄。
图1示出了用户佩戴控制设备的示意图，该控制设备为虚拟现实眼镜。通常，为了获取该控制设备的姿态变化以控制云台的姿态变化，该控制设备上装有惯性测量单元，并以一定的频率(如50HZ)来获取惯性测量单元的姿态数据，再转换成自身的姿态。通常使用俯仰角、偏航角和横滚角来表示姿态，它们分别对应于围绕三维坐标系中的x、y、z轴旋转的角度，范围一般是-180～180度，如图1中所示。
在控制设备开始通过IMU远程控制云台时，可以将云台的姿态和控制设备的IMU的姿态分别记为各自的初始姿态。之后，控制设备定期获取自身的相对于初始姿态的IMU姿态(包括俯仰角、偏航角和横滚角)，并将这三个相对角度传输给云台端。云台端收到这些相对角度后，运动到相对于自身初始姿态的相应的俯仰角、偏航角和横滚角，从而达到云台的相对姿态(即云台的姿态改变)和控制设备的相对姿态(即控制设备的姿态改变)一致的效果。
在控制设备控制云台的过程中，可以同时使用云台上的相机进行录像。如果控制设备的IMU移动不均匀(或者幅度上的变化很快)，或者控制设备的IMU状态通过无线方式传输到云台端有延迟，则会造成云台的移动不平滑，从而拍摄的视频会出现明显的卡顿(不平滑)。
发明内容
为了解决以上问题中的至少一部分，本公开提出对发送给云台的IMU的相对姿态数据进行平滑处理的技术方案。通过该技术方案，能够保证发给云台的IMU控制命令是平滑的，从而使云台能够平滑地移动，最终改善视频拍摄的效果。
根据本公开的一个方面，提供了一种数据处理方法，用于控制无人机的云台。该数据处理方法包括获取目标姿态数据和云台的第一时刻姿态数据，第一时刻姿态数据是云台的当前姿态数据。该数据处理方法还包括计算目标姿态数据与第一时刻姿态数据之间的变化。如果该变化大于特定阈值，则对目标姿态数据进行平滑处理，以计算第二时刻姿态数据。无人机根据第二时刻姿态数据执行对应的操作。例如，无人机可以根据第二时刻姿态数据来调整无人机的云台的姿态。
根据本公开的另一个方面，提供了一种无人机的控制设备。该控制设备包括姿态获取单元，被配置为获取目标姿态数据。该控制设备还包括处理器，被配置为获取第一时刻姿态数据，并计算目标姿态数据与第一时刻姿态数据之间的变化，第一时刻姿态数据是云台的当前姿态数据，以及如果该变化大于特定阈值，则对目标姿态数据执行平滑处理以计算第二时刻姿态数据。无人机可以根据第二时刻姿态数据执行对应的操作，例如调整无人机的云台的姿态。
根据本公开的另一个方面，提供了一种无人机，包括云台、通信单元、姿态传感器和处理器。通信单元被配置为获取目标姿态数据。姿态传感器被配置为获取云台第一时刻姿态数据，第一时刻姿态数据是云台的当前姿态数据。处理器被配置为计算目标姿态数据与第一时刻姿态数据之间的变化，以及如果该变化大于特定阈值，则对目标姿态数据执行平滑处理以计算第二时刻姿态数据。该处理器还被配置为根据第二时刻姿态数据来调整云台的姿态。
根据本公开的另一个方面，提供了一种无人机的控制系统，包括上文所述的控制设备以及包括云台的无人机。该无人机被配置为在该控制设备的控制下调整云台的姿态。
根据本公开的另一个方面，提供了一种无人机的控制系统，包括上文所述的无人机以及控制设备。该控制设备被配置为对无人机进行控制。
根据本公开的另一个方面，提供了一种计算机可读存储介质，存储有 计算机程序。当计算机程序由至少一个处理器运行时，使至少一个处理器执行以下操作：获取目标姿态数据和第一时刻姿态数据，第一时刻姿态数据是云台的当前姿态数据；计算目标姿态数据与第一时刻姿态数据之间的变化；如果该变化大于特定阈值，则对目标姿态数据进行平滑处理，以计算第二时刻姿态数据。
采用本公开的技术方案，能够使控制设备中的惯性测量单元的姿态数据均匀地到达云台，并且该姿态数据在幅度上的变化相对平缓。从而，实现了云台的平滑移动，保证了视频拍摄的效果。
附图说明
通过下文结合附图的详细描述，本公开的上述和其它特征将会变得更加明显，其中：
图1示出了用户佩戴控制设备的示意图。
图2是示出了根据本公开一个实施例的方法的流程图。
图3是示出了根据本公开一个实施例的控制设备的框图。
图4是示出了根据本公开一个实施例的无人机的框图。
图5是示出了根据本公开一个实施例的控制设备和无人机的示意图。
图6是示出了根据本公开一个实施例的控制设备和云台端的交互示意图。
图7是示出了根据本公开一个实施例的计算机可读存储介质的框图。
需要注意的是，附图不一定按比例绘制，重点在于示出本文公开的技术的原理。另外，为了清楚起见，贯穿附图中的相似的附图标记指代相似的元素。
具体实施方式
下面结合附图和具体实施方式对本公开进行详细阐述。应当注意，本公开不应局限于下文所述的具体实施方式。另外，为了简便起见，省略了对与本公开没有直接关联的公知技术的详细描述，以防止对本公开的理解造成混淆。
图2是示出了根据本公开一个实施例的方法的流程图。该方法可以由 控制设备来执行以远程控制无人机。备选地，该方法也可以由无人机自身来执行。例如，可以由无人机中的云台控制器来执行，或者可以通过无人机中其他独立的控制单元来执行。本文中所述的无人机可以包括无人飞行器、无人车、无人船等。
如图2所示，在步骤S210，获取目标姿态数据和云台的第一时刻姿态数据。这里，“目标姿态数据”是指控制设备的惯性测量单元(IMU)的当前姿态数据，其例如可以通过三维坐标系中的一组俯仰角、偏航角和横滚角来表示。“第一时刻姿态数据”是指无人机中的云台的当前姿态数据，其可以通过同一个三维坐标系中的另一组俯仰角、偏航角和横滚角来表示。无人机的云台在一定时间间隔内要从第一时刻姿态调整到目标姿态。
在步骤S220，计算目标姿态数据与第一时刻姿态数据之间的变化。例如，如果目标姿态数据与第一时刻姿态数据都由三维坐标系中的俯仰角、偏航角和横滚角来表示，则可以计算这两组角度之间的差，作为目标姿态数据与第一时刻姿态数据之间的变化。
在步骤S230，如果在步骤S220处计算得到的变化大于特定阈值，则对目标姿态数据进行平滑处理，以计算第二时刻姿态数据，使无人机的云台在一定时间间隔内平滑地从第一时刻姿态调整到目标姿态。这里，“第二时刻姿态数据”描述的是云台在第一时刻之后的下一个时刻的姿态数据。无人机可以根据第二时刻姿态数据执行对应的操作。
之所以要进行平滑处理，主要考虑到控制设备的移动通常不是均匀的。例如，以虚拟现实眼镜作为控制设备为例。当虚拟现实眼镜戴在用户的头上并随着用户的头部一起运动时，由于用户很难平滑地移动虚拟现实眼镜，直接发送给云台的虚拟现实眼镜的IMU姿态数据会呈现不均匀的跳动。在用户的头部运动较剧烈时，这种跳动更为明显，从而云台的运动也会跳动较大。因而，云台上所承载的相机拍出来的视频由于云台跳动较大而效果不好。为此，本公开提出，在控制设备上采集到IMU姿态数据后，不将当前IMU姿态数据立即发送给云台端，而是可以根据之前的云台姿态和当前的IMU姿态数据计算中间逼近的值，并将该逼近的姿态数据发送给云台端。
下面，以三维坐标系中的y轴(偏航角)为例来描述IMU的姿态数据的变化。本领域技术人员可以理解，本文描述的原理同样可以适用于其他方向的姿态数据的计算，例如x轴(俯仰角)和z轴(横滚角)的姿态数 据的计算。
假设控制设备的IMU的上一次的偏航角为Y1,上一次发送给云台的偏航角为S1(也被称为第一时刻姿态数据),而控制设备的IMU的当前偏航角为Y2(也被称为目标姿态数据)。首先确定(Y2-S1)是否大于一个特定阈值。如果(Y2-S1)大于特定阈值(说明云台的目标姿态变化较为剧烈)，则计算：
S2＝S1+(Y2-S1)*factor    (公式1)
其中，S2表示当前要发送给云台端的偏航角(也被称为第二时刻姿态数据)，而factor是一个可以调节的逼近因子常量，0<factor<＝1。当factor越接近1时，逼近速度越快，相应的抖动会较大，但是延迟较小。当factor越接近0时，逼近速度越慢，相应的抖动会较小，但是延迟较大。factor的取值可以根据需要来调整。例如，可以在控制设备的菜单选项里增加一个调节开关，用于调节factor的大小。
优选地，可以一次或多次执行上述公式的计算(即平滑处理)，使S2更好地逼近Y2。
如果(Y2-S1)小于特定阈值(说明IMU的姿态变化较为平缓)，则如下计算S2：
S2＝S1    (公式2)
其中，与上文相同，S2表示当前要发送给云台端的偏航角。
在本文中，“特定阈值”可以根据期望的平滑度来设定。例如，如果希望抖动少一些(从而云台的拍摄会更为平滑)，可以将该阈值设置得较大；相反，如果希望更快速地在云台端体现控制设备的当前姿态，可以将该阈值设置得较小。
备选地，如果(Y2-S1)小于特定阈值，还可以如下计算S2：
S2＝Y2    (公式3)
上式的含义是：由于云台的目标姿态变化较为平缓，可以将IMU的当前姿态数据直接发送给云台端，而不会导致云台上的相机拍摄的画面出现明显抖动。
优选的，当云台的目标姿态变化较为剧烈时，多次执行平滑处理(例如执行上文的公式1的处理)，使S2不断的逼近Y2，直到Y2-S1小于特定阈值。
根据本公开，可以采用不同的算法来执行平滑处理，其原则是不要立即发送IMU的当前姿态数据给云台端，而是发送平滑后的IMU姿态数据。例如，还可以采用如下所述的阶梯式的平滑处理。
首先，将姿态数据的差的绝对值分成N档。假设第i档的上限为D(i)，下限为D(i-1)，D(0)＝0，i＝1,2,3…N。每档对应一个单位移动距离L(n)。仍以IMU姿态数据中的偏航角为例。假设上一次的IMU姿态数据的偏航角为Y1,上一次发送给云台的偏航角为S1,而当前控制设备的IMU姿态数据的偏航角为Y2。仍假设当前要发送给云台的姿态数据的偏航角为S2,则：
当D(i-1)<＝|Y2-S1|<D(i)时，
S2＝S1+L(n)；如果Y2-S1>＝0
S2＝S1-L(n)；如果Y2-S1<0    (公式4)
即，根据本公开的平滑方案可以描述为：
-计算目标姿态数据Y2与第一时刻姿态数据S1的差(Y2-S1)的绝对值，
-如果该绝对值大于特定阈值，则根据该绝对值来确定增量数据，
-如果(Y2-S1)大于零，则将第一时刻姿态数据S1与该增量数据相加以获得第二时刻姿态数据S2；反之，如果(Y2-S1)小于零，则将第一时刻姿态数据S1与该增量数据相减以获得第二时刻姿态数据S2。
例如，本文中的“增量数据”可以包括公式(1)中的比例因子factor与(Y2-S1)的乘积，所述比例因子factor可以根据阈值区间进行预先设定；或者可以包括公式3中的与特定阈值相对应的数值(L(n))，该数值(L(n))可以由用户预先设定。
另外，在控制设备向云台端传输姿态数据的过程中，由于无线环境干 扰等原因，云台端收到的数据可能有延迟。如果云台端在每次收到数据后运行到姿态数据所要求的位置，则可能出现忽快忽慢的移动，从而影响云台上的相机的拍摄效果。为此，本公开提出，可以对云台端收到的姿态数据进行缓存，并且以固定频率向云台发送缓存的姿态数据，从而使云台的姿态变化是匀速的。优选地，可以与控制设备的采集姿态数据的频率相同的频率来发送相应的姿态数据给云台从而云台的运动也更加平滑。
具体地，例如可以在控制设备端创建一个姿态数据队列来缓存这些姿态数据。相应地，可以在控制设备端创建一个定时器来控制发送，以便控制设备以确定频率采集姿态数据以及发送姿态数据给云台端。在每次收到经过平滑处理的姿态数据后，将该姿态数据存入该队列的尾部。在用于控制发送的定时器每次被触发时，从队列头获取一组姿态数据，发送给云台端，以控制云台运动到与所发送的IMU姿态数据相对应的位置。
备选地，也可以在云台端创建姿态数据队列来缓存接收的姿态数据。例如，当从控制设备收到经过平滑处理的姿态数据后，便将该处理后的姿态数据发送给云台端并存入数据队列的尾部。之后，云台端可以从数据队列的头部依次获取缓存的姿态数据，并控制云台运行到该姿态数据所要求的位置。
可以理解，姿态数据队列中的数据不宜过多，否则可能会造成比较大的延迟。优选地，当发现队列中的姿态数据过多时，可以丢弃部分数据(例如队列头的数据)。备选地，可以将用于控制发送的定时器的频率设为高于控制设备端IMU的数据采集(获取)频率。例如，可以将用于控制发送的定时器的频率设为控制设备端IMU的采集(获取)频率的二倍。这样，每当用于控制发送的定时器触发时，就从队列头获取一组数据发送给云台。由于发送频率是获取频率的两倍，使得能够更快地发送缓存的姿态数据，减少队列中的数据。
采用本公开的技术方案，能够使控制设备的姿态变化均匀地到达云台，并且该姿态数据在幅度上的变化相对平缓。从而，实现了云台的平滑移动，保证了视频拍摄的效果。
图3是示出了根据本公开一个实施例的控制设备的框图。如图3所示，控制设备30包括姿态获取单元310和处理器320。作为一个示例，控制设备30可以包括虚拟现实眼镜，数据获取单元310可以包括虚拟现实眼镜中 的惯性测量单元IMU，处理器320可以包括虚拟现实眼镜中的微处理器。然而，本领域技术人员可以理解，控制设备30还可以采取其他多种形式，例如遥控器、体感设备等，而不限于上述示例。
姿态获取单元310被配置为获取目标姿态数据。处理器320被配置为获取第一时刻姿态数据，并计算目标姿态数据与第一时刻姿态数据之间的变化。如果该变化大于特定阈值，则对目标姿态数据执行平滑处理，以计算第二时刻姿态数据。
如上文所述，“目标姿态数据”是指控制设备的惯性测量单元(IMU)的当前姿态数据，“第一时刻姿态数据”是指无人机中的云台的当前姿态数据。例如，它们都可以通过三维坐标系中的一组俯仰角、偏航角和横滚角来表示。这里，“第二时刻姿态数据”描述的是云台在第一时刻之后的下一个时刻的姿态数据，其也可以通过三维坐标系中的一组俯仰角、偏航角和横滚角来表示。
例如，处理器320可以计算姿态获取单元310获取的目标姿态数据Y2与第一时刻姿态数据S1的差的绝对值。如果该差的绝对值大于特定阈值，则根据该差来计算增量数据，并将该增量数据与第一时刻姿态数据相加以获得第二时刻姿态数据。在一个示例中，增量数据可以包括上述公式1中的差(Y2-S1)与比例因子factor的乘积，该比例因子大于0且不大于1。在另一个示例中，增量数据可以包括公式4中的与特定阈值相对应的数值L(n)。
备选地，处理器320还可以被配置为通过一次或多次执行平滑处理使第二时刻姿态数据逼近目标姿态数据。备选地，处理器320还可以被配置为以固定频率发送第二时刻姿态数据。
备选地，控制设备30还可以包括缓存器(图3中未示出)。如上文所述，由于无线环境干扰等原因，云台端收到的数据可能有延迟。如果云台端在每次收到数据后运行到姿态数据所要求的位置，则可能出现忽快忽慢的移动，从而影响云台上的相机的拍摄效果。在此情况下，处理器320可以被配置为：在发送第二时刻姿态数据前，在该缓存器中缓存第二时刻姿态数据。这样，能够以固定频率向云台发送缓存的姿态数据(例如，以与控制设备获取姿态数据的频率相同的频率来发送相应的姿态数据)，从而使云台的姿态变化是匀速的。
图4是示出了根据本公开一个实施例的无人机的框图。如图4所示，无人机40包括云台410、通信单元420、姿态传感器430和处理器440。
云台410上可以承载相机，以拍摄期望的画面。
通信单元420被配置为获取目标姿态数据。姿态传感器430被配置为获取云台的第一时刻姿态数据。“目标姿态数据”和“第一时刻姿态数据”的含义与上文相同，为了简便起见不再重复。
处理器440被配置为计算目标姿态数据与第一时刻姿态数据之间的变化。如果该变化大于特定阈值，则对目标姿态数据执行平滑处理以计算第二时刻姿态数据。然后，处理器440可以根据计算得到的第二时刻姿态数据来调整云台410的姿态，使得云台410上的相机能够更加平稳地拍摄画面。
例如，处理器440可以被配置为：计算目标姿态数据Y2与第一时刻姿态数据S1的差的绝对值。如果该差的绝对值大于特定阈值，则根据该差来计算增量数据，并将该增量数据与第一时刻姿态数据相加以获得第二时刻姿态数据。例如，增量数据可以包括上述公式1中的差(Y2-S1)与比例因子factor的乘积，该比例因子可以对应特定阈值进行设置，其值大于0且不大于1。备选地，增量数据可以包括公式4中的与特定阈值相对应的数值L(n)。
备选地，处理器440可以被配置为通过一次或多次执行平滑处理以使第二时刻姿态数据逼近目标姿态数据。
备选地，处理器440可以被配置为以固定频率发送第二时刻姿态数据。
备选地，无人机40还可以包括缓存器(图4中未示出)。如上文所述，由于无线环境干扰等原因，云台端收到的数据可能有延迟。如果云台端在每次收到数据后运行到姿态数据所要求的位置，则可能出现忽快忽慢的移动，从而影响云台上的相机的拍摄效果。在此情况下，处理器440可以被配置为：在发送第二时刻姿态数据前，在该缓存器中缓存第二时刻姿态数据。这样，能够以固定频率发送缓存的姿态数据(例如，以与控制设备获取姿态数据的频率相同的频率来发送相应的姿态数据)，从而使云台的姿态变化是匀速的。
优选地，处理器440还可以被配置为：如果缓存器中缓存的第二时刻姿态数据达到预定数量，则丢弃缓存的第二时刻姿态数据中的一部分。
优选地，处理器440还可以被配置为：如果缓存器中缓存的第二时刻姿态数据达到预定数量，则按照比目标姿态数据的获取频率更高的发送频率来发送第二时刻姿态数据。该发送频率可以是获取频率的N倍，其中N为大于等于1的整数。例如，可以将发送频率设为获取频率的二倍。由此，能够更快地发送缓存的姿态数据，从而减少队列中的数据。
需要指出的是，处理器440可以以多种方式来实现。例如，处理器440可以包括分离的计算单元和控制单元。在此示例中，计算单元被配置为计算目标姿态数据与第一时刻姿态数据之间的变化，以及如果该变化大于特定阈值则对目标姿态数据执行平滑处理以计算第二时刻姿态数据。而控制单元被配置为根据第二时刻姿态数据来调整云台的姿态。
备选地，处理器440可以包括存储器和微处理器。该存储器被配置为存储指令，该指令在由微处理器运行时使微处理器执行以下操作：计算目标姿态数据与第一时刻姿态数据之间的变化；以及如果该变化大于特定阈值，则对目标姿态数据执行平滑处理以计算第二时刻姿态数据；以及根据第二时刻姿态数据来调整云台的姿态。
下面，参照图5和图6来描述根据本公开的无人机的控制系统。
图5是示出了根据本公开一个实施例的控制设备和无人机的示意图。图5的上半部分示出了无人机的一个图片示例。可以看出，该无人机包括云台，而云台上可以携带一个或更多个摄像头。图5的下半部分示出了一种带有惯性测量单元IMU的控制设备，即虚拟现实眼镜。用户可以佩戴该虚拟现实眼镜，从而控制无人机的飞行。另外，在无人机和虚拟现实眼镜之间，通过虚线指示控制设备向无人机传输控制指令和IMU姿态数据。
图6是示出了根据本公开一个实施例的控制设备和云台端的交互示意图。需要说明的是，图6示出的平滑处理是在控制设备中实现的。然而，根据上文的描述，本领域技术人员可以理解，根据本公开的平滑处理也可以在云台端来实现，例如在云台控制器中实现。
如图6所示，具有IMU的控制设备在定时器的控制下，定期获取IMU的姿态数据。然后，对所获取的IMU的姿态数据执行上文描述的平滑处理，获得处理后的姿态数据。控制设备将处理后的姿态数据发送(例如以无线通信的方式)给云台端。云台端将接收的IMU姿态数据存入IMU姿态数据队列中，并在定时器的控制下从该队列中定期获取IMU姿态数据。然后， 云台控制器可以根据所获取的IMU姿态数据，相应地控制云台自身的姿态。
下面通过两个表格来比较本公开的技术方案相对于现有的技术方案的优点。表1示出了在采用现有的技术方案的情况下发送给云台的命令序列：
时间(小时：分钟：秒.毫秒) 发送的偏航角(单位：度)
12:30:17.348 12.3
12:30:17.368 12.8
12:30:17.426 12.9
12:30:17.432 12.9
12:30:17.438 13.2
12:30:17.448 13.6
12:30:17.488 13.8
12:30:17.490 14.2
表1
可以看出，表1中示出的发送给云台的命令序列的时间间隔不均匀，且幅度变化较大。
表2示出了在采用根据本公开的技术方案的情况下发送给云台的命令序列：
时间(小时：分钟：秒.毫秒) 发送的偏航角(单位：度)
13:13:22.012 15.6
13:13:22.032 15.8
13:13:22.052 16.1
13:13:22.072 16.3
13:13:22.092 16.6
13:13:22.112 16.8
13:13:22.132 17.1
13:13:22.152 17.4
表2
可以看出，表2中示出的发送给云台的命令序列的时间间隔均匀，且幅度变化比较平缓。
采用本公开的技术方案，发送给云台端的IMU姿态数据从时间上看更加均匀，从空间幅度上来看变化更加平滑。这样，云台的运动也更加平滑，使得云台上携带的相机所拍摄的视频也更加平滑，减少了因IMU变化过快 或者变化不均匀所带来的视频卡顿现象。
此外，本公开的实施例可以借助于计算机程序产品来实现。例如，该计算机程序产品可以是计算机可读存储介质。计算机可读存储介质上存储有计算机程序，当在计算设备上执行该计算机程序时，能够执行相关的操作以实现本公开的上述技术方案。
例如，图7是示出了根据本公开一个实施例的计算机可读存储介质70的框图。如图7所示，计算机可读存储介质70包括程序710。该程序710在由至少一个处理器运行时，使得至少一个处理器执行以下操作：获取目标姿态数据和第一时刻姿态数据；计算目标姿态数据与第一时刻姿态数据之间的变化；如果该变化大于特定阈值，则对目标姿态数据进行平滑处理，以计算第二时刻姿态数据，使无人机的云台在一定时间间隔内平滑地从第一时刻姿态调整到目标姿态。这里，“第二时刻姿态数据”描述的是在第一时刻之后的下一个时刻的姿态数据。
本领域技术人员可以理解，本公开的实施例中的计算机可读存储介质70的示例包括但不限于：半导体存储介质、光学存储介质、磁性存储介质、或任何其他的计算机可读存储介质。
上文已经结合优选实施例对本公开的方法和涉及的设备进行了描述。本领域技术人员可以理解，上面示出的方法仅是示例性的。本公开的方法并不局限于上面示出的步骤和顺序。
应该理解，本公开的上述实施例可以通过软件、硬件或者软件和硬件两者的结合来实现。本公开的这种设置典型地提供为设置或编码在例如光介质(例如CD-ROM)、软盘或硬盘等的计算机可读介质上的软件、代码和/或其他数据结构、或者诸如一个或多个ROM或RAM或PROM芯片上的固件或微代码的其他介质、或一个或多个模块中的可下载的软件图像、共享数据库等。软件或固件或这种配置可安装在计算设备上，以使得计算设备中的一个或多个处理器执行本公开实施例所描述的技术方案。
此外，上述每个实施例中所使用的设备的每个功能模块或各个特征可以由电路实现或执行，所述电路通常为一个或多个集成电路。设计用于执行本说明书中所描述的各个功能的电路可以包括通用处理器、数字信号处理器(DSP)、专用集成电路(ASIC)或通用集成电路、现场可编程门阵列(FPGA)或其他可编程逻辑器件、分立的门或晶体管逻辑、或分立的硬件 组件、或以上器件的任意组合。通用处理器可以是微处理器，或者所述处理器可以是现有的处理器、控制器、微控制器或状态机。上述通用处理器或每个电路可以由数字电路配置，或者可以由逻辑电路配置。此外，当由于半导体技术的进步，出现了能够替代目前的集成电路的先进技术时，本公开也可以使用利用该先进技术得到的集成电路。
运行在根据本发明的设备上的程序可以是通过控制中央处理单元(CPU)来使计算机实现本发明的实施例功能的程序。该程序或由该程序处理的信息可以临时存储在易失性存储器(如随机存取存储器RAM)、硬盘驱动器(HDD)、非易失性存储器(如闪速存储器)、或其他存储器系统中。用于实现本发明各实施例功能的程序可以记录在计算机可读记录介质上。可以通过使计算机系统读取记录在所述记录介质上的程序并执行这些程序来实现相应的功能。此处的所谓“计算机系统”可以是嵌入在该设备中的计算机系统，可以包括操作系统或硬件(如外围设备)。
如上，已经参考附图对本发明的实施例进行了详细描述。但是，具体的结构并不局限于上述实施例，本发明也包括不偏离本发明主旨的任何设计改动。另外，可以在权利要求的范围内对本发明进行多种改动，通过适当地组合不同实施例所公开的技术手段所得到的实施例也包含在本发明的技术范围内。此外，上述实施例中所描述的具有相同效果的组件可以相互替代。

Claims (39)

  1. 一种数据处理方法，用于控制无人机的云台，所述数据处理方法包括：
    获取目标姿态数据和云台的第一时刻姿态数据，所述第一时刻姿态数据是云台的当前姿态数据；
    计算所述目标姿态数据与所述第一时刻姿态数据之间的变化；以及
    如果所述变化大于特定阈值，则对所述目标姿态数据进行平滑处理，以得到第二时刻姿态数据，所述无人机根据第二时刻姿态数据执行对应的操作。
  2. 根据权利要求1所述的方法，其中，通过一次或多次执行平滑处理，使所述第二时刻姿态数据逼近所述目标姿态数据。
  3. 根据权利要求1所述的方法，还包括：以固定频率发送所述第二时刻姿态数据。
  4. 根据权利要求3所述的方法，在发送所述第二时刻姿态数据前，将所述第二时刻姿态数据进行缓存。
  5. 根据权利要求4所述的方法，其中，如果缓存的第二时刻姿态数据达到预定数量，则丢弃缓存的第二时刻姿态数据中的一部分。
  6. 根据权利要求4所述的方法，其中，如果缓存的第二时刻姿态数据达到预定数量，则按照比目标姿态数据的获取频率更高的发送频率来发送所述第二时刻姿态数据。
  7. 根据权利要求6所述的方法，其中，所述发送频率是所述获取频率的N倍，N为大于等于1的整数。
  8. 根据权利要求2的方法，其中，所述平滑处理包括：
    计算所述目标姿态数据与第一时刻姿态数据的差的绝对值；以及
    如果所述差的绝对值大于特定阈值，则根据所述差来计算增量数据，并将所述增量数据与第一时刻姿态数据相加以获得第二时刻姿态数据。
  9. 根据权利要求8所述的方法，其中，所述增量数据包括所述差与比例因子的乘积，所述比例因子大于0且不大于1。
  10. 根据权利要求8所述的方法，其中，所述增量数据包括与所述特定 阈值相对应的数值。
  11. 根据权利要求1所述的方法，其中，所述姿态数据包括三维坐标系中的旋转角度。
  12. 根据权利要求1所述的方法，其中，所述无人机根据第二时刻姿态数据来调整所述无人机的云台的姿态。
  13. 一种无人机的控制设备，包括：
    姿态获取单元，被配置为获取目标姿态数据；以及
    处理器，被配置为获取所述第一时刻姿态数据，并计算所述目标姿态数据与所述第一时刻姿态数据之间的变化，所述第一时刻姿态数据是云台的当前姿态数据；以及如果所述变化大于特定阈值，则对所述目标姿态数据执行平滑处理，以计算第二时刻姿态数据；所述无人机根据第二时刻姿态数据执行对应的操作。
  14. 根据权利要求13所述的控制设备，其中，所述处理器被配置为：通过一次或多次执行平滑处理，使所述第二时刻姿态数据逼近所述目标姿态数据。
  15. 根据权利要求13所述的控制设备，其中，所述处理器还被配置为：以固定频率发送所述第二时刻姿态数据。
  16. 根据权利要求14所述的控制设备，还包括缓存器，
    其中，所述处理器被配置为：在发送所述第二时刻姿态数据前，在所述缓存器中缓存所述第二时刻姿态数据。
  17. 根据权利要求14所述的控制设备，其中，所述处理器被配置为：
    计算所述目标姿态获取单元获取的所述目标姿态数据与第一时刻姿态数据的差的绝对值；以及
    如果所述差的绝对值大于特定阈值，则根据所述差来计算增量数据，并将所述增量数据与第一时刻姿态数据相加以获得第二时刻姿态数据。
  18. 根据权利要求17所述的控制设备，其中，所述增量数据包括所述差与比例因子的乘积，所述比例因子大于0且不大于1。
  19. 根据权利要求17所述的控制设备，其中，所述增量数据包括与所述特定阈值相对应的数值。
  20. 根据权利要求13所述的控制设备，其中，所述姿态数据包括三维坐标系中的旋转角度。
  21. 根据权利要求13所述的控制设备，其中，所述姿态获取单元包括惯性测量单元。
  22. 根据权利要求13所述的控制设备，其中，所述控制设备包括虚拟现实眼镜或遥控器。
  23. 根据权利要求13所述的控制设备，其中，所述无人机根据第二时刻姿态数据来调整所述无人机的云台的姿态。
  24. 一种无人机，包括：
    云台；
    通信单元，被配置为获取目标姿态数据；
    姿态传感器，被配置为获取所述云台的第一时刻姿态数据，所述第一时刻姿态数据是云台的当前姿态数据；
    处理器，被配置为计算所述目标姿态数据与所述第一时刻姿态数据之间的变化；以及如果所述变化大于特定阈值，则对所述目标姿态数据执行平滑处理以计算第二时刻姿态数据；以及根据所述第二时刻姿态数据来调整所述云台的姿态。
  25. 根据权利要求24所述的无人机，其中，所述处理器被配置为：通过一次或多次执行平滑处理，使所述第二时刻姿态数据逼近所述目标姿态数据。
  26. 根据权利要求24所述的无人机，其中，所述处理器被配置为：以固定频率发送所述第二时刻姿态数据。
  27. 根据权利要求26所述的无人机，还包括缓存器，其中，所述处理器被配置为：在发送所述第二时刻姿态数据前，在所述缓存器中缓存所述第二时刻姿态数据。
  28. 根据权利要求27所述的无人机，其中，所述处理器被配置为：如果所述缓存器中缓存的第二时刻姿态数据达到预定数量，则丢弃缓存的第二时刻姿态数据中的一部分。
  29. 根据权利要求27所述的无人机，其中，所述处理器被配置为：如果所述缓存器中缓存的第二时刻姿态数据达到预定数量，则按照比目标姿态数据的获取频率更高的发送频率来发送所述第二时刻姿态数据。
  30. 根据权利要求29所述的无人机，其中，所述发送频率是所述获取频率的N倍，N为大于等于1的整数。
  31. 根据权利要求25所述的无人机，其中，所述处理器被配置为：
    计算所述目标姿态数据与第一时刻姿态数据的差的绝对值；以及
    如果所述差的绝对值大于特定阈值，则根据所述差来计算增量数据，并将所述增量数据与第一时刻姿态数据相加以获得第二时刻姿态数据。
  32. 根据权利要求31所述的无人机，其中，所述增量数据包括所述差与比例因子的乘积，所述比例因子大于0且不大于1。
  33. 根据权利要求31所述的无人机，其中，所述增量数据包括与所述特定阈值相对应的数值。
  34. 根据权利要求24所述的无人机，其中，所述姿态数据包括三维坐标系中的旋转角度。
  35. 根据权利要求24所述的无人机，其中，所述处理器包括计算单元和控制单元，
    所述计算单元被配置为：计算所述目标姿态数据与所述第一时刻姿态数据之间的变化；以及如果所述变化大于特定阈值，则对所述目标姿态数据执行平滑处理以计算第二时刻姿态数据；
    所述控制单元被配置为：根据所述第二时刻姿态数据来调整所述云台的姿态。
  36. 根据权利要求24所述的无人机，其中，所述处理器包括存储器和微处理器，所述存储器被配置为存储指令，所述指令在由所述微处理器运行时使所述微处理器执行以下操作：
    计算所述目标姿态数据与所述第一时刻姿态数据之间的变化；以及如果所述变化大于特定阈值，则对所述目标姿态数据执行平滑处理以计算第二时刻姿态数据；以及根据所述第二时刻姿态数据来调整所述云台的姿态。
  37. 一种无人机的控制系统，包括：
    根据权利要求13-23中任一项所述的控制设备；以及
    包括云台的无人机，所述无人机被配置为在所述控制设备的控制下调整所述云台的姿态。
  38. 一种无人机系统，包括：
    根据权利要求24-36中任一项所述的无人机；以及
    控制设备，被配置为对所述无人机进行控制。
  39. 一种计算机可读存储介质，存储有计算机程序，当所述计算机程序 由至少一个处理器运行时，使所述至少一个处理器执行根据权利要求1-12中任一项所述的方法。
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