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WO2014076844A1 - Système à déplacement autonome et dispositif de commande - Google Patents

Système à déplacement autonome et dispositif de commande Download PDF

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Publication number
WO2014076844A1
WO2014076844A1 PCT/JP2012/079970 JP2012079970W WO2014076844A1 WO 2014076844 A1 WO2014076844 A1 WO 2014076844A1 JP 2012079970 W JP2012079970 W JP 2012079970W WO 2014076844 A1 WO2014076844 A1 WO 2014076844A1
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WIPO (PCT)
Prior art keywords
map
coordinates
correction
autonomous mobile
travel locus
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.)
Ceased
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PCT/JP2012/079970
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English (en)
Japanese (ja)
Inventor
大島　章
山本　健次郎
一野瀬　亮子
幸彦 小野
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Hitachi Ltd
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Hitachi Ltd
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Priority to PCT/JP2012/079970 priority Critical patent/WO2014076844A1/fr
Priority to JP2014546831A priority patent/JP5930346B2/ja
Publication of WO2014076844A1 publication Critical patent/WO2014076844A1/fr
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
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
    • G05D1/0272—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means comprising means for registering the travel distance, e.g. revolutions of wheels
    • 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
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
    • G05D1/0274—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means using mapping information stored in a memory device
    • 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
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS

Definitions

  • the present invention relates to a technology of an autonomous movement system and a control device that estimates a self-position based on environmental information and a map and autonomously moves based on the estimated self-position.
  • Realization of an autonomous mobile device requires a system equipped with a self-position estimation technique for accurately grasping where the autonomous mobile device itself is located and not making a mistake in the traveling position.
  • environmental information such as image information, shape information, and coordinates prepared in advance is used as a map for self-position estimation (hereinafter also simply referred to as a map).
  • the autonomous mobile device identifies the position of the autonomous mobile device itself on the map by comparing environmental information acquired from the surroundings of the autonomous mobile device itself with a map prepared in advance. For this reason, self-position estimation accuracy improves by generating a map with high accuracy, and the autonomous mobile device can perform stable autonomous movement.
  • it is desirable that the information held in the map is acquired from the autonomous mobile device.
  • maps generated based on environmental information acquired from the sky using satellites and aircraft have a much different environment appearance than autonomous mobile devices that move on the ground (floor surface or road surface). It cannot be used as a map for moving.
  • a map generated based on environmental information acquired from a distant point even at the same height is not likely to be used as a map because it is likely to look different from the autonomous mobile device. For this reason, it is common to manually run an autonomous mobile device (maneuvered by a person) in advance in an environment subject to autonomous movement, acquire surrounding environment information, and generate a map based on this environment information. Has been done. By doing in this way, it becomes possible to generate a map with high certainty in collation during autonomous movement.
  • a map generation method for accurately connecting and integrating maps obtained by dividing into a plurality of maps is disclosed (for example, see Patent Document 1 and Patent Document 2).
  • the technique described in Patent Document 1 extracts one or more feature points from the environment, derives a constraint relationship by associating the feature points between the divided maps, and generates one wide-area map based on this. is doing.
  • Patent Document 1 acquires and divides an autonomously moving environment as a partial map without duplication, and determines and corrects the mutual positional relationship based on the constraint relationship of each feature information. By doing so, one map is generated.
  • the partial maps are set for each narrow area having a characteristic environmental shape such as an intersection or a corner.
  • the constraint relationship is configured such that the map is generated by the user inputting the positional relationship of the adjacent partial maps, the parallelism of the shape, or the like based on the design drawing of the surrounding environment.
  • the constraint relationship refers to a relationship in which positions are constrained between a plurality of pieces of information in order to link the locations between different environmental information including the same location.
  • different environmental information including the same point includes, for example, environmental information of the same point in different partial maps, environmental information of the same point acquired by different routes and means in one or more partial maps, etc. This is called a restraint relationship.
  • the constraint means a relationship such as position / posture between two or more pieces of information.
  • the coordinates on one map are It shows what kind of positional relationship it is with respect to which coordinate on the other map.
  • a constraint between GPS (Global Positioning System) positioning information and movement coordinates such as odometry is also referred to as a constraint relationship as to which point a certain movement coordinate is in the absolute coordinate system in the GPS positioning information.
  • Patent Document 2 is based on the screen output provided in the autonomous mobile device and the interface operated by a human by button input, thereby associating connection points between a plurality of maps into one wide area map. Is generated.
  • the technology described in Patent Document 2 acquires an environment in which autonomous movement is performed as a partial map in the same manner as the technology described in Patent Document 1.
  • the partial maps overlap each other little by little, and one wide-area map is generated by the user setting the constraint relationship between the positions and orientations of adjacent partial maps by screen output or button input.
  • the autonomous mobile device is configured to change partial maps and move to a target point.
  • the technique described in Patent Document 2 when there is a change in the shape of the environment or the travel route, only the partial map including the point is acquired again and the map is generated again.
  • the technique described in Patent Document 1 makes it difficult to extract feature information such as parallelism because there are fewer straight portions when there is a complex-shaped structure, making it difficult to use the feature information.
  • the technique described in Patent Document 1 causes a situation where the partial maps cannot be accurately connected. Therefore, the technique described in Patent Document 1 cannot be applied to wide-area map creation when there is a complex-shaped structure.
  • the technique described in Patent Document 1 is based on the premise that the road surface of the environment is horizontal, and does not take into account the case of having a slope or a three-dimensional intersection. Therefore, in the technique described in Patent Document 1, if the environment information includes three-dimensional information, a shift (error) occurs in the height direction in the generated map.
  • the technique described in Patent Document 2 distortion remains in each partial map.
  • the distortion is an error caused by a measurement error such as odometry.
  • the technique described in Patent Document 2 can be used for a wide-area map generation because a simple constraint relationship may be defined as long as it is a line-like traveling locus.
  • the technique described in Patent Document 2 needs to further subdivide the partial map and set a large number of constraint relationships. is there.
  • the technique described in Patent Document 2 cannot be applied to wide-area map generation for dealing with a mesh-like traveling locus.
  • the technique described in Patent Document 2 is based on the premise that the road surface of the environment is horizontal as in the technique described in Patent Document 1, and the case where the environment information such as slopes and three-dimensional intersections has three-dimensional information. Not considered.
  • the present invention has been made in view of such a background, and an object of the present invention is to improve the certainty in connection of partial maps.
  • the present invention performs a first correction for deforming a travel locus based on absolute coordinates, and further detects an overlapping travel region in which the corrected travel tracks are close to each other. After associating the relative coordinates on the travel locus in the travel region, a second correction for further correcting the travel locus is performed.
  • FIG. 10 is a diagram (part 1) illustrating a conceptual diagram of determination of availability of environmental information acquired from the sky. It is FIG. (2) which shows the conceptual diagram of the availability determination of the environmental information acquired from the sky. It is a flowchart which shows the procedure of the connection of the partial map which concerns on this embodiment. It is a figure for demonstrating the connection method of the partial map which concerns on this embodiment.
  • the autonomous mobile system according to the present embodiment makes it possible to accurately derive the movement coordinates by correcting the movement coordinates (movement locus) when the autonomous movement apparatus is manually driven, including the height direction. .
  • the autonomous mobile system according to this embodiment generates a map for self-position estimation by accurately connecting and integrating shape information (partial maps) obtained by dividing even if the environment of autonomous movement is wide area By enabling the technology, a highly accurate self-position estimation technology is realized.
  • the partial map is a map related to a partial region obtained by dividing the region where the autonomous mobile device travels, and is set so that overlapping regions (inter-map overlapping regions) are generated between the partial maps.
  • the inter-map overlap area will be described later with reference to FIG.
  • FIG. 1 is a diagram illustrating a configuration example of an autonomous mobile system according to the present embodiment.
  • the autonomous mobile system 1 includes an environment information acquisition unit (environment information acquisition unit) 101, a travel locus correction unit (travel locus correction unit) 102, a partial map generation unit (map generation unit) 103, and a map generation unit (map generation unit) 104.
  • the environment information acquisition unit 101 is configured by combining a plurality of measurement units.
  • the environment information acquisition unit 101 includes, for example, a laser distance sensor, a monocular or compound eye camera system, a GPS sensor, an atmospheric pressure sensor, and the like.
  • laser survey information may be acquired from an image acquired from an aircraft or a satellite, or a laser surveying device (not shown) provided outside the autonomous mobile device 10.
  • the environment information acquisition unit 101 may acquire information manually surveyed separately.
  • the environment information acquisition unit 101 may be combined with a device that acquires information inside the autonomous mobile device 10 in addition to a device that acquires external information from the autonomous mobile device 10.
  • an environment information acquisition unit 101 for example, it is possible to acquire movement amount information that can be acquired from a moving mechanism such as a wheel, crawler, or leg for movement of the autonomous mobile device 10, and momentum information such as angular velocity or acceleration.
  • a moving mechanism such as a wheel, crawler, or leg for movement of the autonomous mobile device 10
  • momentum information such as angular velocity or acceleration.
  • movement coordinates There are inertial measurement sensors. Movement amount information that can be acquired from movement mechanisms such as wheels, crawlers, and legs, and momentum information such as angular velocity and acceleration are referred to as movement coordinates.
  • Each environment information acquired by the environment information acquisition unit 101 (GPS coordinates by the GPS sensor, surrounding shape information by the laser distance sensor, shape information acquired from the aircraft, etc.) is associated with the movement coordinates and stored in the environment information. Stored in the unit 121.
  • the environment information acquisition unit 101 includes a relative coordinate that indicates the relative position of the autonomous mobile device during movement, an absolute coordinate that indicates the absolute position of the autonomous mobile device during movement, and environmental information of the surrounding area during movement. And get
  • the environment information storage unit 121 also stores environment information (manual environment information) obtained when the autonomous mobile device 10 is steered and traveled by the user, and the autonomous mobile device 10 moves autonomously.
  • the environment information (autonomous environment information) obtained when doing so is also stored.
  • the self-position estimation unit 105 described later is used for estimation of the self-position, or the path generation unit 106 described later is used for arrangement of surrounding structures and road surfaces. It is used when grasping the situation and moving an appropriate route.
  • the travel locus correction unit 102 corrects the travel locus (described later in detail) based on a plurality of types of environment information acquired by the environment information acquisition unit 101.
  • the partial map generation unit 103 generates a partial map by complementing the shape data included in the environment information based on the travel locus corrected by the travel locus correction unit 102.
  • the partial map generation unit 103 may generate a partial map using only manual environment information, or may generate a partial map using both manual environment information and autonomous environment information.
  • the partial map generation unit 103 may generate a partial map by directly using environmental information from a device that acquires environmental information provided outside the autonomous mobile device 10 (not shown).
  • the map generation unit 104 connects a plurality of partial maps generated by the partial map generation unit 103 to generate a map for self-position estimation.
  • the map generation unit 104 may generate / update a map online when the autonomous mobile device 10 moves, or may generate / update a map offline.
  • the generated map is stored in the map storage unit 122.
  • the self-position estimation unit 105 estimates the self-position by matching (matching) the environment information acquired during autonomous movement with the map stored in the map storage unit 122.
  • a self-position estimation technique in addition to the above-described technique, self-position estimation based on accumulation of information using the vehicle body movement amount or other internal information may be used, or self-position estimation based on GPS positioning information is used. May be. Further, by combining these self-position estimation methods and applying a filtering process (for example, Kalman filtering or an application method thereof), the self-position estimation results by the respective methods may be merged. In association with the map, techniques used for image processing and point cloud processing are used.
  • the route generation unit 106 extracts surrounding obstacles, road surface steps, pedestrian positions, and pedestrian movement speeds from environmental information acquired during autonomous movement, and performs graph search processing and motion model simulation processing. By using it, the moving direction and speed of the autonomous mobile device 10 are determined.
  • the movement control unit 107 moves the autonomous mobile device 10 based on the moving direction and speed of the autonomous mobile device 10 determined by the route generation unit 106. Thereby, the autonomous mobile device 10 automatically moves from one point to another target point.
  • the environment information acquisition unit 101, the self-position estimation unit 105, the route generation unit 106, the movement control unit 107, the environment information storage unit 121, and the map storage unit 122 may be mounted on the autonomous mobile device 10. Conceivable. Similarly, it is conceivable that the environment information storage unit 121, the travel locus correction unit 102, the partial map generation unit 103, the map generation unit 104, and the map storage unit 122 are mounted on the control device 20 installed in a control station or the like. .
  • the units 101 to 107, 121, and 122 are not necessarily mounted on the autonomous mobile device 10 and the control device 20 as shown in FIG. 1.
  • all the units 101 to 107, 121, and 122 are all mounted on the autonomous mobile device 10.
  • the environment information acquisition unit 101, the travel locus correction unit 102, the self-position estimation unit 105, the route generation unit 106, the movement control unit 107, and the environment information storage unit 121 are mounted on the autonomous mobile device 10. Also good.
  • the environmental information acquired by the autonomous mobile device 10 is transmitted to the control device 20. Then, after the control device 20 corrects the travel locus based on the environmental information, a partial map is generated, and the partial map is further connected to generate a wide-area map. Then, the control device 20 sends the generated map to the autonomous mobile device 10.
  • the autonomous mobile device 10 estimates its own position based on the sent map and moves.
  • FIG. 2 is a diagram illustrating a hardware configuration example of the autonomous mobile device and the control device according to the present embodiment.
  • FIG. 2A is a diagram illustrating a hardware configuration example of the autonomous mobile device 10.
  • a CPU Central Processing Unit
  • a memory 202 such as a ROM (Read Only Memory)
  • a communication interface 203 is connected to each other via a bus 204.
  • a program is stored in the memory 202, and when the CPU 201 executes the program, the self-position estimation unit 105, the route generation unit 106, the movement control unit 107, and the like of FIG.
  • FIG. 2B is a diagram illustrating a hardware configuration example of the control device 20.
  • a CPU 211 a CPU 211, a RAM (Random Access Memory) 212, a ROM 213, a communication interface 214, and an HD (Hard Disk) 215 are connected to each other via a bus 216.
  • a program stored in the ROM 213 and the HD 215 is expanded in the RAM 212, and the CPU 211 executes the program, thereby realizing the travel locus correction unit 102, the partial map generation unit 103, the map generation unit 104, and the like.
  • FIG. 3 is a flowchart showing the procedure of map generation processing according to the present embodiment. This process is a process performed during manual travel.
  • the environment information acquisition unit 101 acquires environment information related to a partial area of the traveling road (S101).
  • the travel locus correction unit 102 performs a travel locus correction process for correcting the travel locus based on the movement coordinates, which is one of the environment information (S102). Step S102 will be described later with reference to FIGS.
  • the moving coordinates are coordinate data acquired by dead reckoning, that is, wheel odometry, gyro odometry, visual odometry (hereinafter simply referred to as odometry).
  • trajectory is a locus
  • the partial map generation unit 103 generates a partial map by complementing the shape data obtained from the environment information based on the corrected travel locus (S103).
  • the map generation unit 104 connects the partial maps based on the corrected travel locus, generates a wide area map (S104), and stores the map in the map storage unit 122. Step S104 will be described later with reference to FIGS.
  • FIG. 4 is a flowchart showing the procedure of the autonomous movement process according to the present embodiment.
  • the environment information acquisition unit 101 acquires environment information (S201).
  • the self-position estimation unit 105 estimates the self-position by collating the environment information acquired in step S201 with the map stored in the map storage unit 122 (S202).
  • the route traveled by the autonomous mobile device 10 based on the stationary obstacle, the moving obstacle information, the self-location information, the map, and the like extracted from the environment information acquired in step S201 by the route generation unit 106. Is generated (S203).
  • the movement control unit 107 moves the autonomous mobile device 10 according to the generated route (S204).
  • FIG. 5 is a diagram showing a detailed procedure of the travel locus correction process (step S102 in FIG. 3) according to the present embodiment.
  • the travel locus correction unit 102 performs first correction, which is correction of the travel locus based on the movement coordinates, using GPS positioning information that is one of the environment information (S301).
  • the movement coordinates are obtained by integrating movement amount information and momentum information (pointing to angular velocity, acceleration, and geomagnetic direction).
  • the movement coordinates accumulate errors due to slippage between the movement mechanism and the road surface, sensor measurement error, and the like. That is, in the movement coordinates, the error increases as the movement distance increases.
  • the trajectory connecting the movement coordinates is the travel trajectory.
  • FIG. 6 is a diagram illustrating an example of a travel locus based on movement coordinates according to the present embodiment.
  • a travel locus 300 in FIG. 6 in the present embodiment, a travel locus based on three-dimensional movement coordinates having information in the height direction based on three-dimensional odometry is assumed.
  • the travel locus 300 in FIG. 6 does not consider errors due to odometry, which will be described later.
  • the travel locus 300 actually includes errors as described later. Therefore, the traveling locus correction unit 102 corrects the traveling locus in step S301 in FIG. 5 to three-dimensionally correct the horizontal direction and the height direction of the movement coordinates.
  • the moving coordinates are not limited to the three-dimensional coordinates as shown in FIG. 6, and may be two-dimensional coordinates based on two-dimensional odometry.
  • step S301 The processing in step S301 will be described later with reference to FIGS.
  • the traveling locus correction unit 102 associates the movement coordinates of the overlapping traveling area, which is an area where the autonomous mobile device 10 travels in duplicate (S302).
  • the process of step S302 will be described later with reference to FIG.
  • the travel locus correction unit 102 performs the same process as in step S301 again using the result of step S302, and performs the second correction for correcting the travel locus (S303).
  • FIGS. 7 to 18 Details of the travel locus correction and map generation by the travel locus correction unit 102, the partial map generation unit 103, and the map generation unit 104 according to the present embodiment will be described.
  • FIGS. 7 to 18 show two-dimensional movement coordinates.
  • FIG. 7 is a diagram illustrating an example of a travel area of the autonomous mobile device according to the present embodiment.
  • the autonomous mobile system 1 acquires environmental information in the partial area 610 and maps a partial map obtained by mapping the partial area 610. Generate. As shown in FIG. 18, a plurality of partial maps are generated so that overlapping regions are generated in different partial regions 610, 901, and 902. And the autonomous mobile system 1 finally produces
  • the partial area 610 is an area where the autonomous mobile device 10 acquires environment information in one run. Reference numerals 611 to 613, 621, and 622 will be described later.
  • FIG. 8 is a diagram illustrating an example of a travel locus according to the present embodiment.
  • the autonomous mobile device 10 has moved along the route 701 in a single travel (for example, manual travel).
  • the true movement coordinates acquired by this traveling should be the movement coordinates on the route 701. That is, the travel locus should be the shape of the route 701.
  • a traveling locus based on the movement coordinates before correction is indicated by reference numeral 711.
  • errors are accumulated in the movement coordinates acquired by the environment information acquisition unit 101 due to the effects of slippage between the movement mechanism and the road surface, measurement errors of the sensor, and the like.
  • the travel locus 711 based on the movement coordinates acquired by the environment information acquisition unit 101 is distorted in shape. That is, the travel locus 711 based on the movement coordinates acquired by the environment information acquisition unit 101 is deviated from the true route 701.
  • the traveling locus correction unit 102 first corrects the traveling locus 711 based on the uncorrected movement coordinates by the constraint based on the GPS positioning information (hereinafter, more specifically referred to as GPS coordinates). .
  • the constraint based on the GPS coordinate indicates where the coordinate of each point of the movement coordinate corresponds to in an arbitrary absolute coordinate system (for example, a world coordinate system such as latitude, longitude, and altitude).
  • the travel locus correction unit 102 corrects the travel coordinates by deforming the travel locus 711 based on the travel coordinates before correction and acquiring the shape of the travel locus that minimizes the deviation from the GPS coordinates.
  • the travel locus correction unit 102 defines, for example, the error as a density function based on errors that can occur based on the physical meaning of each constraint. Then, the traveling locus correction unit 102 may consider that all constraints are satisfied to the maximum by changing the positional relationship of the movement coordinates so that the value based on the density function is maximized or minimized. Good. That is, the travel locus correction unit 102 considers that all constraints are satisfied to the maximum by the optimization process.
  • a method of solving as an optimization problem of simultaneous equations such as a Graph-SLAM (Simultaneous Location And Mapping) method may be used, or a random relationship with respect to the traveling locus may be used.
  • a technique based on a procedure that satisfies constraints by superimposing minute corrections by trial and error may be used.
  • FIG. 9 to FIG. 11 a specific procedure for deforming the travel locus 711 before correction to obtain the corrected travel locus will be described in detail.
  • FIG. 9 is a diagram showing a detailed procedure of the first correction according to the present embodiment.
  • a travel locus 711 based on a movement coordinate 721 before correction of the travel locus (referred to as a movement coordinate 721 before correction as appropriate) is obtained.
  • GPS coordinates are acquired as reference numeral 731.
  • “ ⁇ ” marks indicate movement coordinates measured by odometry
  • “x” marks indicate GPS coordinates (GPS coordinates).
  • the movement coordinates 721 before correction and the GPS coordinates 731 are associated with each other (for example, movement coordinates 721a and GPS coordinates 731a before correction, movement coordinates 721b and GPS coordinates 731b before correction, and the like).
  • the environment information acquisition unit 101 acquires information (movement coordinates) for generating a traveling locus of the autonomous mobile device and absolute coordinates (GPS coordinates) associated with a predetermined position of the traveling locus.
  • the traveling locus correction unit 102 obtains a corrected traveling locus indicated by a broken line by deforming the traveling locus 711 based on the movement coordinates 721 before correction and the GPS coordinates 731. For example, the travel locus correction unit 102 generates a corrected travel locus 741 that minimizes an error evaluation value defined from the movement coordinates 721 and the GPS coordinates 731 before correction. As the travel locus 711 is corrected, the movement coordinates 721 on the travel locus 711 are also corrected.
  • FIG. 10 is a diagram illustrating an example of an error evaluation value (first error evaluation value) used for the first correction according to the present embodiment.
  • FIG. 10 is an enlarged view of a part of the travel locus shown in FIG. 9, and the same components as those in FIG. 9 are denoted by the same reference numerals.
  • a point where the GPS coordinate 731 is not associated with the uncorrected movement coordinate 721 (hereinafter referred to as the movement coordinate 721 as appropriate) is a point where the GPS coordinate could not be acquired.
  • the travel locus correction unit 102 obtains the existence probability of a GPS coordinate defined by a density function with respect to the distance from the acquired GPS coordinate 731, and an area indicated by a value (2 ⁇ ) obtained by multiplying the standard deviation ( ⁇ ) by 2 (2 ⁇ region 732) is calculated for each GPS coordinate 731. Then, the travel locus correction unit 102 draws a line segment 733 from the point closest to the movement coordinate 721 in the 2 ⁇ region 732 to the movement coordinate 721. The travel locus correction unit 102 calculates the line segment 733 for each pair of movement coordinates 721 and GPS coordinates 731. At this time, the length of the line segment 733 is set to “0” at a point where the GPS coordinate 731 cannot be acquired.
  • the traveling locus correction unit 102 sets the square sum of each line segment 733 as an error evaluation value, and deforms the traveling locus 711 before correction (referred to as traveling locus 711 as appropriate) so that the square sum becomes the smallest. By doing so, a corrected travel locus 741 (FIG. 9) is obtained. At this time, it is preferable that the travel locus is deformed so that the travel locus 711 is as linear as possible except for a corner (for example, a portion where each of the travel locus 711 has a certain size or more).
  • the traveling locus correction unit 102 slightly deforms the traveling locus 711 to obtain a total value of the line segment 733 as an error evaluation value, and then deforms the traveling locus 711 further slightly to obtain the total value of the line segment 733. Is repeated to obtain a corrected travel locus 741 in which the total value of the line segment 733 is the smallest.
  • the reason for using such a method is that the GPS coordinate 731 also includes an error.
  • RTK-GPS Real Time Kinematic-GPS
  • D-GPS Downlink-GPS
  • RTK-GPS Real Time Kinematic-GPS
  • D-GPS Downlink-GPS
  • RTK-GPS Real Time Kinematic-GPS
  • D-GPS can be re-positioned while the autonomous mobile device 10 is moving, and can be easily used because the number of necessary satellites is small.
  • the height of the moving coordinate may be corrected by using the height information of the partial area 610 (FIG. 7) measured in advance with an aircraft or the like together with the GPS coordinates. The method will be described with reference to FIG.
  • FIG. 11 is a diagram illustrating an example of an error evaluation value used for correction in consideration of the height information of the traveling path acquired from the aircraft (hereinafter referred to as aircraft information 751) in addition to the GPS coordinates 731.
  • aircraft information 751 is a diagram illustrating an example of an error evaluation value used for correction in consideration of the height information of the traveling path acquired from the aircraft (hereinafter referred to as aircraft information 751) in addition to the GPS coordinates 731.
  • aircraft information 751 is a diagram illustrating an example of an error evaluation value used for correction in consideration of the height information of the traveling path acquired from the aircraft (hereinafter referred to as aircraft information 751) in addition to the GPS coordinates 731.
  • aircraft information 751 is a diagram illustrating an example of an error evaluation value used for correction in consideration of the height information of the traveling path acquired from the aircraft (hereinafter referred to as aircraft information 751) in addition to the GPS coordinates 731.
  • aircraft information 751 is a diagram illustrating an example of an error evaluation value used for correction in consideration of
  • the travel locus correction unit 102 calculates a 2 ⁇ region 752 for the aircraft information 751 in the same manner as the GPS coordinate 731 in FIG. 10, and the uncorrected movement coordinate 721 (appropriately, the movement coordinate 721 in the 2 ⁇ region 752).
  • a line segment 753 is drawn on the movement coordinate 721 from the point closest to the above.
  • the travel locus correction unit 102 calculates the line segment 753 for each pair of movement coordinates 721 and aircraft information 751. At this time, the length of the line segment 753 is “0” at a point where the aircraft coordinates 751 cannot be acquired.
  • the traveling locus correction unit 102 sets the total value of all the line segments 733 and all the line segments 753 as an error evaluation value (first error evaluation value), and the traveling locus before correction so that the total value becomes the smallest. 711 (referred to as travel locus 711 as appropriate) is modified. Thereby, the traveling locus correction unit 102 obtains a corrected traveling locus 741 (FIG. 9).
  • the travel locus may be deformed so that the travel locus 711 is as linear as possible except at a corner (for example, each portion formed by the travel locus 711 has a certain size or more).
  • the traveling locus correction unit 102 may add weight according to the accuracy of the GPS coordinates 731 and the aircraft information 751. For example, if the aircraft information 751 is more accurate than the GPS coordinate 731, the traveling locus correction unit 102 increases the weight of the line segment 753.
  • the correction of the travel locus shown in FIGS. 10 and 11 is an example, and other methods may be used.
  • the corrected travel locus 741 may be obtained by using a genetic algorithm, a neural network, or the like. The above is the travel locus correction processing in step S301 in FIG.
  • the movement coordinates are sequentially corrected as in the prior art, the movement coordinates are not corrected at locations where GPS coordinates are not acquired, such as tunnels, and errors are accumulated during that time. And since GPS coordinates can be acquired, the correction is made suddenly from the state in which the errors up to that point are accumulated, so that the travel locus becomes discontinuous.
  • the GPS coordinates are acquired from a place where the GPS coordinates are not acquired in order to correct the travel locus in consideration of the influence of other places. A continuous running track can be obtained even when the vehicle moves to a place.
  • the travel locus correction unit 102 calculates the first error evaluation value based on the absolute coordinates, and deforms the travel locus of the autonomous mobile device obtained from the relative coordinates based on the first error evaluation value. Thus, the first correction for correcting the travel locus is performed.
  • FIG. 12 is a diagram for explaining the detailed procedure of associating the movement coordinates of the overlapping travel area (step S302 in FIG. 5).
  • the travel trajectory correction unit 102 causes the autonomous mobile device 10 to pass through the vicinity of the corrected travel trajectory 741 generated in step S301 as shown in FIG. It is possible to obtain a region (overlapping traveling region 771) that can be estimated as being. That is, the traveling locus correction unit 102 detects the overlapping traveling region 771 by detecting a region where the corrected traveling locus is close.
  • the travel locus correction unit 102 has detected that the regions that are close to each other so that the tracks constituting the travel locus that has been corrected by the first correction are located, so that the autonomous mobile devices have traveled in duplicate. Detect overlapping running areas that are areas
  • the traveling locus correction unit 102 calculates the relative positional relationship between the movement coordinates 761 and 762, for example, by comparing the surrounding shape data obtained at the respective points of the movement coordinates 761 and 762.
  • shape data is shape data, such as a building acquired with a laser distance sensor, for example.
  • the shape data is information included in the environment information.
  • the travel locus correction unit 102 obtains the shape data (the thick line portion 765 in FIG. 12B) acquired by the autonomous mobile device 10 at the movement coordinates 761, and FIG. The shape data (the thick line portion 766 in FIG. 12C) acquired by the autonomous mobile device 10 at the movement coordinates 762 as shown in FIG.
  • the movement coordinates in the overlapping traveling area 771 are associated with each other, and the restriction between the moving coordinates in the overlapping traveling area 771 is determined.
  • the traveling locus correction unit 102 selects a plurality of relative coordinates on the traveling locus in the overlapping traveling region, and compares the environment information associated with each selected relative coordinate with each other to select each of the selected relative coordinates.
  • a first relative positional relationship between relative coordinates is calculated. Specifically, it is calculated by the processing in step S302 that the relative positional relationship between the movement coordinates 761 and 762 is a positional relationship as shown in FIG. 12D (broken arrows in FIG. 12D).
  • the constraint (relative positional relationship) between the two movement coordinates associated with each other in the overlapping travel area 771 is that one movement coordinate (for example, reference numeral 761) and the other movement coordinate ( For example, it has a meaning as to what value the position / posture of the autonomous mobile device 10 at 762) should satisfy.
  • the travel locus correction unit 102 associates the shape or pattern in the environment information obtained from the environment information acquisition unit 101 by an ICP (Iterative Closest Point) method in point cloud processing or a template matching method in image processing. Correspondence between moving coordinates is performed.
  • ICP Intelligent Closest Point
  • the traveling locus correction unit 102 can correct the movement coordinates so as to satisfy the constraints of the relative coordinate system.
  • a variation error occurs in the constraint based on the GPS coordinates, it is possible to obtain moving coordinates that are not repeatedly arranged at a location where the information on the same point is shifted. That is, the error does not disappear completely even in the result of the travel locus correction performed in step S301 in FIG.
  • the movement coordinates corrected in this way include an error, the overlapping traveling point is not recognized as another point.
  • the travel locus correction unit 102 first performs rough correction of the travel locus by eliminating the accumulation of errors from the travel locus 711 (moving coordinates) using GPS coordinates and aircraft information. First, do it. By doing in this way, it becomes possible to restrict the maximum value of the error that the moving coordinate has to the extent of the GPS coordinate error. Furthermore, in the overlapping traveling area in one traveling, the error at each associated point can be suppressed to the extent of the GPS coordinate error. Therefore, the certainty at the time of producing
  • the traveling locus correction unit 102 performs the second correction using the GPS coordinates again using the movement coordinates in which the overlapping traveling regions 771 are associated (step S303 in FIG. 5). That is, the travel locus correction unit 102 calculates a second error evaluation value based on both the calculated first relative positional relationship and the absolute coordinates, and uses the travel locus as the second error evaluation value. By performing the deformation based on the second correction, the second correction for correcting the travel locus is performed. At this time, the travel locus 711 is corrected again by the same procedure as in step S301.
  • FIG. 13 is a diagram illustrating an example of an error evaluation value (second error evaluation value) used for the second correction according to the present embodiment.
  • the travel locus correction unit 102 draws a line segment 783 from the movement coordinate 781 associated with the movement coordinate 721 in step S302 to the movement coordinate 721. At this time, the length and direction of the line segment 783 are drawn so as to be a relative positional relationship between the movement coordinates 721 and 781 calculated in step S302.
  • the travel locus correction unit 102 calculates the line segment 783 for each movement coordinate 721.
  • the travel locus correction unit 102 uses the total value of all the line segments 733 and all the line segments 783 as an error evaluation value, and deforms the travel locus 741 after the first correction so that the total value is minimized. Then, the second correction is performed. At this time, it is desirable to increase the weight of the line segment 783 (indicated by a thick line in FIG. 13). Similarly to FIG. 10, the travel locus may be deformed so that the travel locus 711 is as linear as possible except at a corner (for example, each of the travel locus 711 is a certain size or more).
  • the traveling locus correction unit 102 may draw a line segment 783 between the 2 ⁇ region and the movement coordinate 781 and use the total value of all the line segments 733 and all the line segments 783 as an error evaluation value.
  • the movement coordinates associated with each other in a relative positional relationship are paired for each transfer coordinate, but association between a plurality of movement coordinates may be used.
  • a line segment having a length based on the relative positional relationship may be used as the error evaluation value.
  • the travel locus correction unit 102 does not use the result of step S301, but performs processing from the beginning (that is, uses the travel locus before correction instead of using the corrected travel locus). It is desirable.
  • trajectory used by this embodiment is made into three types of the movement information acquired by the autonomous mobile device 10, GPS coordinates, and the environment information by an aircraft, it is not restricted to these three types, There may be four or more types. Moreover, as long as it is an absolute coordinate, information other than the GPS coordinate or the environment information by the aircraft may be used. In addition, it is desirable to set the traveling route of the autonomous mobile device 10 in advance so that the overlapping traveling area is as large as possible.
  • FIG. 14 is a diagram illustrating a change in the travel locus associated with the first correction and the second correction according to the present embodiment.
  • a travel trajectory 711 in FIG. 14A is a travel trajectory before the first correction, and is a movement coordinate itself acquired from odometry.
  • 741 shown in FIG. 14B is obtained by performing the first correction shown in FIGS. 9 to 11 on the travel locus 711.
  • the travel locus 741 is closer to the true travel locus (the shape of the route 701 in FIG. 8) than the travel locus 711, but the influence of errors in absolute coordinates such as GPS coordinates remains. In other words, the error in the travel locus 741 is suppressed to the extent of an error in absolute coordinates such as GPS coordinates.
  • the travel locus correction unit 102 detects an overlapping travel region for the travel locus 741 after the first correction, and the second correction shown in FIGS. 12 and 13 is performed, so that FIG. A travel locus 791 shown in FIG.
  • the traveling locus 791 is a true traveling locus (the shape of the route 701 in FIG. 8) than the traveling locus 711 or 741 It is close to.
  • a traveling path 601 that is an object of autonomous movement includes a region 612 in which a structure 611 such as a tree or a building exists, and a region 613 in which there is no structure around. .
  • balloons 621 and 622 from the areas 612 and 613 in FIG. 7 show bird's-eye views of the areas 612 and 613, respectively.
  • the environment information acquired by the aircraft is referred to as the sky environment information.
  • the aircraft information described above (the travel path height information acquired from the aircraft) is information included in the sky environment information.
  • FIG. 15 and FIG. 16 are diagrams showing conceptual diagrams for determining whether or not to use environment information acquired from the sky.
  • object shape data is used as environment information.
  • the aircraft information described above uses this shape data as height information.
  • FIG. 15 is a diagram related to a region where a structure 611 such as a tree or a building exists in the vicinity of the autonomous mobile environment (the region 612 in FIG. 7), and FIG.
  • FIG. 16 illustrates a structure such as a tree or a building around the autonomous mobile environment.
  • FIG. 8 is a diagram relating to a region in which there is no such as region 613 in FIG.
  • the environmental information is acquired from the aircraft 800 that acquires environmental information from the sky and the autonomous mobile device 10 that acquires environmental information while traveling on the ground. Is done.
  • the environment information obtained from the autonomous mobile device 10 is referred to as ground environment information.
  • a shape 821 shown in FIGS. 15A and 15B is a cross section of shape data obtained from the sky environment information in the region of FIG.
  • a shape 822 in FIGS. 15A and 15C is a cross section of shape data obtained from the ground environment information in the region of FIG.
  • a shape 831 shown in FIGS. 16A and 16B is a cross section of shape data obtained from the sky environment information in the region of FIG.
  • a shape 832 in FIGS. 16A and 16C is a cross section of shape data obtained from the ground environment information in the region of FIG.
  • shape data (shape) obtained from the sky environment information 821) and the shape data (shape 822) obtained from the ground environment information are different shapes.
  • the shape of the shape data (shape 832) obtained from the ground environment information is similar to (shape 831).
  • the shape data obtained from the sky environment information differs from the shape data obtained from the ground environment information depending on whether or not a structure exists in the surroundings.
  • the traveling locus correction unit 102 associates a shape / pattern or the like between the shape data obtained from the sky environment information and the shape data obtained from the ground environment information, and determines whether or not they are similar. To do. In this way, the travel locus correction unit 102 matches the height information in the movement coordinates acquired by the autonomous mobile device 10 with the height information acquired from the aircraft 800 or the like in the sky (the degree of coincidence is a predetermined value or more). Whether or not to do so can be determined. That is, the traveling locus correction unit 102 can determine whether or not the height in the traveling locus (moving coordinates) can be corrected based on the height information obtained from the sky environment information.
  • the traveling locus correction unit 102 The height information in the travel locus (movement coordinates) is not corrected with the height information based on the information.
  • the shape data (shape 831) based on the sky environment information is similar to the shape data (shape 832) obtained from the ground environment information.
  • the travel locus is corrected with the height information based on the environmental information.
  • the traveling locus correction unit 102 compares the shape information acquired by the aircraft with the shape information acquired by the autonomous mobile device itself, and the shape information acquired by the aircraft and the shape acquired by the autonomous mobile device itself. When the information matches, it is possible to correct the travel locus using the height information acquired by the aircraft at that point. This process is performed before step S301 in FIG.
  • the method for associating the shape data based on the ground environment information and the shape data based on the sky environment information used here may be any method.
  • the traveling locus correction unit 102 may calculate the sky environment information and the ground environment information. You may calculate a similarity directly between shape data.
  • the travel locus correction unit 102 may separate the road surface and the wall surface (three-dimensional object) from the ground environment information, and determine from the density of the wall surface existing in the surroundings and the similarity of the positions.
  • the traveling locus correction unit 102 may use the degree of similarity of the road surface pattern.
  • the edge (height change) of the shape data and the edge (luminance change) of the image may be associated with each other.
  • the constraint may be the absolute coordinate system, and the coordinate system used in the sky environment information and the terrestrial rights cooperative information
  • the coordinate system used in is different from that of the coordinate system, the constraint of both coordinate systems is used for correction as the constraint of the relative coordinate system.
  • the processes in FIGS. 15 and 16 can be omitted.
  • the travel locus including the correction of the height information can be corrected. Further, by matching the shape data acquired by the autonomous mobile device 10 with the shape data acquired from an aircraft or the like, and determining whether or not the height information acquired from the aircraft can be used, the accuracy in correcting the travel locus can be improved. Can be improved. Note that by using shape data acquired from a device flying over the aircraft 800 or the like, shape data of a wide area can be acquired at a time.
  • the partial map generation unit 103 adds shape data acquired from a laser distance sensor or the like as necessary based on the corrected movement coordinates of the partial region, and generates a partial map (see FIG. 3 step S103). That is, the partial map generation unit 103 generates a map based on the travel locus corrected by performing the second correction. And this map (partial map) is produced
  • the travel locus correction unit 102 can correct the three-dimensional travel locus acquired in one run and generate a partial map based on the corrected travel locus.
  • the movement coordinates in each partial map have no constraint on each other. That is, it is in a state in which it is not known what positional relationship the moving coordinates between the partial maps are.
  • the positioning error tends to be different because the arrangement of GPS satellites is greatly different.
  • the movement coordinate constraint between the partial maps is specified by the method shown in FIGS. 17 and 18.
  • FIG. 17 is a flowchart showing a partial map connection procedure according to this embodiment. This process shows details of step S104 in FIG. Details of each process will be described later with reference to FIG.
  • the map generation unit 104 associates movement coordinates in an overlapping area between maps that are overlapping areas between partial maps (S401). That is, each partial map is set with an inter-map overlapping area that is an overlapping area between adjacent maps.
  • the map generation unit 104 performs a third correction for correcting the travel locus in each partial map to be processed based on the movement coordinates associated in step S401 (S402). Subsequently, the map generation unit 104 combines the partial maps based on the movement coordinates on the travel locus corrected in step S402 (S403).
  • FIG. 18 is a diagram for explaining a partial map connection method according to the present embodiment.
  • a plurality of partial maps (partial regions 610, 901, 902) obtained by dividing the region where the autonomous mobile device travels are acquired so that an inter-map overlapping region that is an overlapping region between the partial maps is generated.
  • a partial map (partial region) is acquired so that the entire travel path 601 is covered.
  • the maximum value of the error is already limited for the movement coordinates in each of the partial areas 610, 901, and 902. Therefore, it is possible to obtain constraints between the moving coordinates in the relative coordinate system based on the above-described correspondence between the overlapping portions.
  • the map generation unit 104 further corrects the travel trajectory so as to satisfy the constraint of the relative coordinate system between the partial maps, and the moving coordinates that do not shift the connection points in the partial areas 610, 901, and 902 are obtained. obtain.
  • the movement coordinates 1111 exist on the corrected travel locus 1110 in the partial area 610 and the movement coordinates 1121 and 1122 exist on the corrected travel locus 1120 in the partial area 901.
  • the map generation unit 104 calculates a relative positional relationship (second relative positional relationship, that is, a constraint relationship) of the movement coordinates 1111, 1121, and 1122 from shape data such as surrounding buildings.
  • the map generation unit 104 compares the environment information in the inter-map overlap area with each other for adjacent maps, thereby obtaining a second relative position that is a relative positional relationship between the relative coordinates in the inter-map overlap area. Calculate the positional relationship.
  • the map generation unit 104 associates the movement coordinates in the inter-map overlap area using the same method as in step S302 in FIG.
  • the association of the positional relationship of the movement coordinates corresponds to the process of step S401 in FIG.
  • the map generation unit 104 determines the positional relationship between different points on the travel locus in the partial map sharing the map overlap region by comparing the surrounding environment information in the map overlap region. To do. By doing so, it is possible to specify the constraint (positional relationship) between the coordinates in the inter-map overlap region, so that the partial maps can be accurately combined without human intervention.
  • the map generation unit 104 corrects the travel locus so that the positional relationship of the movement coordinates 1111, 1121, and 1122 on the map becomes the determined positional relationship (third correction).
  • the map generation unit 104 deforms one or both traveling trajectories in adjacent maps so that each relative coordinate in the inter-map overlap area has the calculated second relative positional relationship, thereby generating a map.
  • a third correction for correcting the travel locus at is performed. This correction of the travel locus corresponds to step S402 in FIG. That is, the map generation unit 104 performs a third correction for correcting the travel locus on the partial map that is the processing target so that the points on the partial map have the determined positional relationship.
  • the map generation unit 104 translates or rotates the travel trajectory so that the movement coordinates on the travel trajectories are in a determined positional relationship.
  • the map generation unit 104 may adjust the influence on the constraint according to the distance / distance to each moving coordinate. In other words, the correction may be performed in accordance with the amount of distance between the travel coordinates and the movement coordinates, that is, after adjusting by weighting the distance between the distance of travel and the movement coordinates.
  • the map generation unit 104 increases the weight of the positional relationship (constraint relationship) of the movement coordinates between the partial maps, and then performs the processing of steps S301 to S303 in FIG. 5 to correct the travel locus again. It may be. By doing in this way, the certainty in the connection of a partial map can be improved.
  • the certainty of the connection of the partial maps can be improved by further correcting the traveling trajectory so as to satisfy the constraint of the relative coordinate system between the partial maps.
  • the map generation unit 104 then combines the partial maps based on the movement coordinates on the travel locus corrected in step S402 (step S403 in FIG. 17). In other words, the map generation unit 104 combines the maps by combining the relative coordinates in the travel locus corrected by the third correction in the inter-map overlap area.
  • the map generation unit 104 completes a map for self-position estimation by arranging shape data such as buildings around each moving coordinate obtained as necessary.
  • the completed map includes road surface height information (height information) at each point. Note that, even if they are at the same point, if the heights of the respective movement coordinates do not completely match due to errors or the like, the map generation unit 104 calculates an average value from adjacent values and calculates the height at an arbitrary point. You may consider that.
  • the movement coordinates when moving autonomously are corrected by the above-described method, and the corrected driving is performed.
  • the environment is acquired by traveling many times on the travel path 601 (FIG. 7) that is the target of autonomous movement, constraints are increased, so that variation in each error can be reduced by averaging. By doing in this way, a map can be highly accurate.
  • the travel locus correction unit 102 determines the constraints between the movement coordinates obtained by the autonomous mobile device 10 traveling the same place many times during the autonomous movement, using the processing of steps S301 to S303 in FIG. Thus, it is possible to obtain a corrected travel locus with higher accuracy.
  • environment information such as moving coordinates increases too much, it may be reduced by thinning or compression, and information with low existence probability when acquiring environment information multiple times is assumed to be noise such as moving objects You may make it delete preferentially.
  • working locus is performed based on a movement coordinate and a GPS coordinate
  • environmental information by GPS and aircraft is used to correct the height information in the travel locus.
  • the present invention is not limited to this, and environmental information measured by other autonomous mobile devices 10 may be used. Good.
  • the travel locus may not be represented by a line as in the present embodiment.
  • the travel locus may be displayed as a point sequence.
  • Each of the above-described configurations, functions, units 101 to 107, storage units 121 and 122, etc. may be realized by hardware by designing a part or all of them, for example, with an integrated circuit. Further, as shown in FIG. 2, the above-described configurations, functions, and the like may be realized by software by interpreting and executing a program that realizes each function by a processor such as the CPU 201, 211. Information such as programs, tables, and files for realizing each function is stored in the memory 202, the ROM 213, and the HD 215 as shown in FIG.
  • control lines and information lines are those that are considered necessary for explanation, and not all control lines and information lines are necessarily shown on the product. In practice, it can be considered that almost all configurations are connected to each other.
  • the error of the movement coordinate can be suppressed to the extent of the error of the GPS coordinate, so that the certainty of the partial map connection can be improved. Further, by performing the process of step S301 in FIG. 5 and correcting the overall travel locus, even if there is a point where GPS coordinates or aircraft information cannot be obtained, the originally continuous travel locus is discontinuous. Can be prevented.
  • step S301 in FIG. 5 of the present embodiment makes it possible to detect the overlapping traveling area, and it is possible to specify the constraint (relative positional relationship) between the movement coordinates in the overlapping traveling area in step S302.
  • the second correction is performed after associating the movement coordinates, so that the error of the movement coordinates can be made more accurate. It can be corrected.
  • steps S301 to S303 in FIG. 5 it is possible to associate the movement coordinates in the inter-map overlap area between the partial maps without the user's hand.
  • the travel locus corrected in this embodiment By generating a partial map using the travel locus corrected in this embodiment and combining the partial maps, it is possible to combine with high accuracy and generate a highly accurate wide area map. .
  • the height information in the movement coordinates By including the height information in the movement coordinates, it is possible to correct the travel locus including the height direction.
  • the movement coordinates are based on dead reckoning or odometry, the travel locus from the viewpoint of the autonomous mobile device 10 can be corrected.
  • realization of this embodiment can be made easy by using general latitude and longitude for an absolute coordinate system.
  • height information can be easily obtained by using environmental information obtained from an aircraft as height information.
  • the accuracy in correcting the height information is determined by matching the shape data acquired by the autonomous mobile device 10 with the shape data acquired from the aircraft or the like to determine whether or not the height information acquired from the aircraft can be used. Can be improved.

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Abstract

La présente invention aborde le problème de l'accroissement de la fiabilité des liaisons entre des cartes partielles. La présente invention est caractérisée en ce qu'elle comprend : une unité (101) d'obtention d'informations d'environnement qui associe et obtient des coordonnées relatives, des coordonnées absolues ainsi que des informations se rapportant à l'environnement ambiant ; et une unité (102) de correction de trajectoires de circulation. L'unité (102) de correction de trajectoires de circulation : calcule une première valeur d'évaluation d'erreur basée sur les coordonnées absolues ; effectue une première correction qui, grâce à la déviation de la trajectoire de circulation en fonction de la première valeur d'évaluation d'erreur, corrige la trajectoire de circulation ; détecte une zone de chevauchement de circulation où les trajectoires de circulation qui ont été corrigées par la première correction se rapprochent ; grâce à une comparaison réciproque des unités d'informations d'environnement dans la zone de chevauchement de circulation, calcule des relations de position relative entre chacune des coordonnées relatives sélectionnées ; calcule une seconde valeur d'évaluation d'erreur basée sur les relations de position relative et sur les coordonnées absolues ; et, grâce à la déviation de la trajectoire de circulation en fonction de la seconde valeur d'évaluation d'erreur, effectue une seconde correction qui corrige la trajectoire de circulation.
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