WO2025069386A1 - 移動体の制御装置、移動体の制御方法、およびプログラム - Google Patents

移動体の制御装置、移動体の制御方法、およびプログラム Download PDF

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Publication number
WO2025069386A1
WO2025069386A1 PCT/JP2023/035663 JP2023035663W WO2025069386A1 WO 2025069386 A1 WO2025069386 A1 WO 2025069386A1 JP 2023035663 W JP2023035663 W JP 2023035663W WO 2025069386 A1 WO2025069386 A1 WO 2025069386A1
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WO
WIPO (PCT)
Prior art keywords
moving body
objects
user
area
target trajectory
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Pending
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PCT/JP2023/035663
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English (en)
French (fr)
Japanese (ja)
Inventor
燦心 松▲崎▼
美紗 小室
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Honda Motor Co Ltd
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Honda Motor Co Ltd
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Priority to JP2025548399A priority Critical patent/JPWO2025069386A1/ja
Priority to PCT/JP2023/035663 priority patent/WO2025069386A1/ja
Priority to CN202380101668.2A priority patent/CN121729653A/zh
Publication of WO2025069386A1 publication Critical patent/WO2025069386A1/ja
Anticipated expiration legal-status Critical
Pending legal-status Critical Current

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    • 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
    • G01C21/20—Instruments for performing navigational calculations
    • 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
    • G05D1/40—Control within particular dimensions
    • G05D1/43—Control of position or course in two dimensions [2D]

Definitions

  • the present invention relates to a control device for a moving object, a control method for a moving object, and a program.
  • robots that guide users to desired locations or transport luggage are known (see, for example, Patent Document 1).
  • the robots described above refer to a movement speed database that associates maximum movement speeds with each area in the environment, and move at a speed that is up to the set maximum movement speed.
  • the present invention was made in consideration of these circumstances, and one of its objectives is to provide a control device for a moving body, a control method for a moving body, and a program that can efficiently generate a target trajectory for a robot.
  • a control device for a moving body includes a recognition unit that recognizes one or more objects present around the moving body and a user of the moving body based on an image capturing the situation around the moving body; a generation unit that generates a target trajectory for following the user based on an index value related to the position of the recognized one or more objects; and a control unit that controls a movement mechanism of the moving body so that the moving body moves along the target trajectory, and the generation unit narrows down the objects for which the index value is taken into consideration depending on whether each of the recognized one or more objects is present in a first area extending between the moving body and the user or in a second area located outside the first area, and generates the target trajectory.
  • the generation unit when an object among the one or more recognized objects is present in the first region, the generation unit generates the target trajectory by taking into account an index value related to the position of the object, regardless of whether the object is stationary or moving.
  • the generation unit when an object among the one or more recognized objects is present in the second region, the generation unit generates the target trajectory taking into account an index value related to the position of the object only when the object is moving.
  • a method for controlling a moving body includes a computer that recognizes one or more objects present around the moving body and a user of the moving body based on an image capturing the situation around the moving body, generates a target trajectory for following the user based on index values related to the positions of the recognized one or more objects, controls a movement mechanism of the moving body so that the moving body moves along the target trajectory, and generates the target trajectory depending on whether each of the recognized one or more objects is present in a first region extending between the moving body and the user, or in a second region located outside the first region.
  • a program storing a program according to another aspect of the present invention causes a computer to recognize one or more objects present around a moving body and a user of the moving body based on an image capturing the situation around the moving body, generate a target trajectory for following the user based on index values relating to the positions of the recognized one or more objects, control a movement mechanism of the moving body so that the moving body moves along the target trajectory, and generate the target trajectory depending on whether each of the recognized one or more objects is present in a first area extending between the moving body and the user or in a second area located outside the first area.
  • the target trajectory of the robot can be generated efficiently.
  • FIG. 1 is a diagram showing an example of a configuration of a mobile body system 1 including a mobile body 100.
  • FIG. FIG. 2 is a diagram for explaining an example of a usage mode of a moving body 100.
  • FIG. 13 is a diagram for explaining a guidance mode.
  • FIG. 2 is a perspective view showing a moving body 100.
  • FIG. 2 is a diagram illustrating an example of a functional configuration of a moving object 100.
  • FIG. 2 is a diagram showing an overview of the processing executed by the risk distribution prediction unit 204 and the trajectory generation unit 206.
  • 11 is a diagram showing an example of a first area AR1 and a second area AR2 set by a trajectory generating unit 206 when generating a trajectory.
  • FIG. 4 is a flowchart showing an example of a flow of processing executed by a control device 200.
  • FIG. 1 is a diagram showing an example of the configuration of a mobile body system 1 including a mobile body 100.
  • the mobile body system 1 includes, for example, one or more terminal devices 2, a management device 10, an information providing device 20, and one or more mobile bodies 100. These communicate, for example, via a network NW.
  • the network NW is any network, such as a LAN, a WAN, or an Internet line.
  • the terminal device 2 is, for example, a computer device such as a smartphone, a tablet terminal, etc.
  • the terminal device 2 requests the provision of authority to use the mobile object 100 from the management device 10 and obtains information indicating that the use has been permitted, for example, based on a user operation.
  • the management device 10 In response to a request from the terminal device 2, the management device 10 grants the user of the terminal device 2 the authority to use the mobile object 100 and manages reservations for the use of the mobile object 100.
  • the management device 10 generates and manages schedule information that associates, for example, preregistered user identification information with the date and time of reservations for the use of the mobile object 100.
  • the information providing device 20 provides the mobile body 100 with the location of the mobile body 100, the area in which the mobile body 100 moves, and map information about the surrounding area. In response to a request from the mobile body 100, the information providing device 20 may generate a trajectory to the destination of the mobile body 100 and provide the generated trajectory to the mobile body 100.
  • FIG. 2 is a diagram for explaining an example of the manner of use of the mobile body 100.
  • the mobile body 100 is placed, for example, at a predetermined position in a facility or a town.
  • the user can operate an operation unit (not shown) of the mobile body 100 to start using the mobile body 100, or can operate the terminal device 2 to start using the mobile body 100.
  • the user starts using the mobile body 100 and puts the luggage in a storage unit of the mobile body 100. Then, the mobile body 100 moves together with the user so as to autonomously follow the user.
  • the user can continue shopping or head to the next destination with the luggage stored in the mobile body 100.
  • the mobile body 100 moves together with the user while moving on a sidewalk or a crosswalk on a roadway.
  • the mobile body 100 can move in an area where pedestrians can pass, such as a roadway and a sidewalk.
  • the mobile body 100 may be used in indoor or outdoor facilities or private grounds, such as shopping centers, airports, parks, and theme parks, and is capable of moving through areas where pedestrians can pass through.
  • the moving body 100 may be capable of moving autonomously in modes such as a guidance mode or an emergency mode in addition to (or instead of) the following mode in which it follows the user as described above.
  • FIG. 3 is a diagram for explaining the guidance mode.
  • the guidance mode is a mode in which the user is guided to a destination specified by the user, and the vehicle autonomously moves in front of the user at the user's moving speed to guide the user.
  • the mobile body 100 guides the user to the location of the product. This allows the user to easily find the specific product.
  • the mobile body 100 or the information providing device 20 holds information in which the locations of products, stores, and facilities in the shopping center are associated with map information, and map information of the shopping center.
  • This map information includes detailed map information including the width of roads and passageways.
  • the emergency mode is a mode in which the mobile unit 100 moves autonomously to seek help from nearby people or facilities if something unusual happens to the user (e.g., the user falls) while moving with the user.
  • the mobile unit 100 may move while maintaining a close but not too far distance from the user.
  • FIG. 4 is a perspective view showing the moving body 100.
  • the forward direction of the moving body 100 is the positive x direction
  • the backward direction of the moving body 100 is the negative x direction
  • the width direction of the moving body 100 is the positive y direction
  • the left direction based on the positive x direction is the positive y direction
  • the right direction is the negative y direction
  • the height direction of the moving body 100 which is perpendicular to the x and y directions, is the positive z direction.
  • the mobile body 100 for example, comprises a base body 110, a door section 112 provided on the base body 110, and wheels (first wheel 120, second wheel 130, and third wheel 140) attached to the base body 110.
  • wheels first wheel 120, second wheel 130, and third wheel 140
  • a user can open the door section 112 to put luggage into a storage section provided on the base body 110 or take luggage out of the storage section.
  • the first wheel 120 and second wheel 130 are driving wheels
  • the third wheel 140 is an auxiliary wheel (driven wheel).
  • the mobile body 100 may be capable of moving using a configuration other than wheels, such as caterpillar tracks.
  • a cylindrical support 150 extending in the positive z direction is provided on the positive z direction surface of the base 110.
  • a camera 180 that captures an image of the surroundings of the moving body 100 is provided on the positive z direction end of the support 150.
  • the position at which the camera 180 is provided may be any position other than the above.
  • Camera 180 is, for example, a camera capable of capturing images of the periphery of moving body 100 at a wide angle (e.g., 360 degrees). Camera 180 may include multiple cameras. Camera 180 may be realized, for example, by combining multiple 120-degree cameras or multiple 60-degree cameras.
  • FIG. 5 is a diagram showing an example of the functional configuration of the moving body 100.
  • the moving body 100 further includes a first motor 122, a second motor 132, a battery 134, a brake device 136, a steering device 138, a communication unit 190, and a control device 200.
  • the first motor 122 and the second motor 132 are operated by power supplied to the battery 134.
  • the first motor 122 drives the first wheel 120
  • the second motor 132 drives the second wheel 130.
  • the first motor 122 may be an in-wheel motor provided in the wheel of the first wheel 120
  • the second motor 132 may be an in-wheel motor provided in the wheel of the second wheel 130.
  • the brake device 136 outputs a brake torque to each wheel based on instructions from the control device 200.
  • the steering device 138 includes an electric motor.
  • the electric motor for example, applies a force to a rack and pinion mechanism based on instructions from the control device 200 to change the direction of the first wheel 120 or the second wheel 130, thereby changing the course of the moving body 100.
  • the communication unit 190 is a communication interface for communicating with the terminal device 2, the management device 10, or the information providing device 20.
  • the control device 200 includes, for example, a recognition unit 202, a risk distribution prediction unit 204, a trajectory generation unit 206, a drive control unit 208, and a storage unit 220.
  • the recognition unit 202, the risk distribution prediction unit 204, the trajectory generation unit 206, and the drive control unit 208 are realized by, for example, a hardware processor such as a CPU (Central Processing Unit) executing a program (software). Some or all of these components may be realized by hardware (including circuitry) such as an LSI (Large Scale Integration), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a GPU (Graphics Processing Unit), or may be realized by cooperation between software and hardware.
  • LSI Large Scale Integration
  • ASIC Application Specific Integrated Circuit
  • FPGA Field-Programmable Gate Array
  • GPU Graphics Processing Unit
  • the program may be stored in advance in a storage device (a storage device having a non-transient storage medium) such as a hard disk drive (HDD) or a flash memory, or may be stored in a removable storage medium (a non-transient storage medium) such as a DVD or a CD-ROM, and may be installed by mounting the storage medium in a drive device.
  • the storage unit 220 is realized by a storage device such as a HDD, a flash memory, or a random access memory (RAM).
  • the storage unit 220 stores map information 222 referenced by the moving body 100.
  • the map information 222 is, for example, map information such as the location of the moving body 100 provided by the information providing device 20, the area in which the moving body 100 moves, and the surrounding area.
  • a part or all of the functional configuration included in the control device 200 may be included in another device.
  • the moving body 100 may communicate with another device and cooperate to control the moving body 100.
  • the recognition unit 202 recognizes the position (distance from the mobile body 100 and direction relative to the mobile body 100) and the state of the speed, acceleration, etc. of objects around the mobile body 100 based on, for example, an image captured by the camera 180. Objects include traffic participants (pedestrians) and obstacles in facilities and on roads.
  • the recognition unit 202 recognizes and tracks the user of the mobile body 100. For example, the recognition unit 202 tracks the user based on an image (e.g., a face image of the user) captured by the user who registered when using the mobile body 100, or a face image of the user (or a feature amount obtained from the face image of the user) provided by the terminal device 2 or the management device 10.
  • the recognition unit 202 recognizes gestures made by the user.
  • the mobile body 100 may be provided with a detection unit different from the camera, such as a radar device or LIDAR.
  • the recognition unit 202 recognizes the situation around the mobile body 100 using the detection results of the radar device or LIDAR instead of (or in addition to) the image.
  • the risk distribution prediction unit 204 sets a risk, which is an index value indicating the degree to which the moving body 100 should not enter or approach, for the object (and its surrounding area) recognized by the recognition unit 202.
  • a risk is an index value indicating the degree to which the moving body 100 should not enter or approach, for the object (and its surrounding area) recognized by the recognition unit 202.
  • the higher the risk value the more the moving body 100 should not enter or approach, and the closer the value is to zero, the more favorable it is for the moving body 100 to pass through. Therefore, generally, the closer to the position of the recognized object, the higher the risk value, while the farther away from the position of the recognized object, the smaller the risk value. However, this relationship may be reversed.
  • the risk is an example of a "position-related index value" in the claims.
  • the risk distribution prediction unit 204 may set risks not only for the present time, but also for future time points specified at regular time intervals, such as the current time t, after ⁇ t (time t+ ⁇ t), after 2 ⁇ t (time t+2 ⁇ t), etc.
  • the risk distribution prediction unit 204 predicts the risk at each future time point based on the change in the position of the moving target that is continuously recognized by the recognition unit 202.
  • the trajectory generating unit 206 generates a trajectory to the destination based on the risk predicted by the risk distribution predicting unit 204.
  • the destination refers to the user itself to be followed or a predetermined point in the vicinity of the user when the mobile body 100 is in the following mode.
  • the destination refers to, for example, the point of a product or facility set by the user.
  • the user specifies the point of the product or facility, and the mobile body 100 checks the point of the specified product or facility against the map information 222, and sets the point of the product or facility identified as a result of the checking as the destination.
  • the point set by the user when the mobile body 100 is in the guidance mode, if the point set by the user is far from the current location of the mobile body 100, the point set by the user may be set as the final destination, and a point within a predetermined range from the current location may be set as a provisional destination. Also, in the guidance mode, the user does not necessarily have to set the destination, and the mobile body 100 may predict the direction in which the user moves and move autonomously in front of the user at the user's moving speed. In this case, the destination of the mobile body 100 may be a point within a predetermined range in front of the user.
  • the trajectory generation unit 206 generates multiple trajectories for reaching the destination, finds the risk for each trajectory point that constitutes each trajectory, and calculates the sum of the found risks as the risk of the trajectory. If the risk of each trajectory point meets a preset criterion (for example, if the risk of each trajectory point is equal to or less than a threshold value Th1) or if the risk of the trajectory meets a preset criterion (for example, if the sum of the risks is equal to or less than a threshold value Th2), the trajectory generation unit 206 adopts the trajectory that meets the criterion as the target trajectory along which the moving body 100 will move.
  • a preset criterion for example, if the risk of each trajectory point is equal to or less than a threshold value Th1
  • Th2 if the sum of the risks is equal to or less than a threshold value
  • the drive control unit 208 controls the movement mechanisms such as the motors (first motor 122, second motor 132), the brake device 136, and the steering device 138 so that the moving body 100 travels along the trajectory generated by the trajectory generation unit 206.
  • FIG. 6 is a diagram showing an overview of the processing executed by the risk distribution prediction unit 204 and the trajectory generation unit 206.
  • FIG. 6 shows, as an example, a case where the moving body 100 is traveling in a following mode, that is, the user U itself is set as the destination.
  • the risk distribution prediction unit 204 sets, as an example, a risk for objects other than the user U and the moving body 100 on a bird's-eye view with an ellipse or circle based on the traveling direction and speed as contour lines, and sets a constant value of risk for an immovable area BD such as a wall.
  • R (OB1) is the risk of a stationary object (a person standing there) OB1
  • R (OB2) is the risk of a moving object (pedestrian) OB2
  • R (OB3) is the risk of a moving object (pedestrian) OB3
  • R (OB4) is the risk of a moving object (pedestrian) OB4. Since the pedestrian continues to move, a risk is set at a position different from the current time for each future time point.
  • R(OB2)_t is the risk of object OB2 in a control cycle
  • R(OB2)_t + ⁇ t is the risk of object OB2 in the next control cycle
  • R(OB2)_t + ⁇ 2t is the risk of object OB2 in the next control cycle.
  • R(BD) is the risk of the unmovable area BD. In the figure, the darkness of the hatching indicates the risk value, and the darker the hatching, the greater the risk.
  • the trajectory generation unit 206 generates multiple trajectories from the moving body 100 to the destination (i.e., user U), and in Figure 6, trajectories TP1 and TP2 are generated as an example.
  • the trajectory generation unit 206 finds the risk for each trajectory point constituting each of the trajectories TP1 and TP2, and calculates the sum of the found risks as the risk of the trajectory. In the case of FIG.
  • the trajectory generation unit 206 calculates the sum of the risk value r(TP1)_t+ ⁇ t at time t+ ⁇ t and the risk value r(TP1)_t+2 ⁇ t at time t+2 ⁇ t for the trajectory TP1, r(TP1)_t+ ⁇ t+r(TP1)_t+2 ⁇ t, and calculates the sum of the risk value r(TP2)_t+ ⁇ t at time t+ ⁇ t and the risk value r(TP2)_t+2 ⁇ t at time t+2 ⁇ t for the trajectory TP2, r(TP2)_t+ ⁇ t+r(TP2)_t+2 ⁇ t, respectively.
  • the trajectory generation unit 206 compares the risk value of the trajectory TP1 with the risk value of the trajectory TP2, and since the risk value of the trajectory TP1 is a positive value while the risk value of the trajectory TP2 is zero, the trajectory TP2 is adopted as the target trajectory.
  • the risk distribution prediction unit 204 sets risks for objects recognized by the recognition unit 202 and their surrounding areas, and the trajectory generation unit 206 selects the trajectory with the smallest risk value from among multiple candidate trajectories.
  • the trajectory generation unit 206 performs route calculations taking into account the risks of all objects recognized by the recognition unit 202, it will have to perform calculations even for objects with an extremely low risk of contact, such as objects that are relatively far away from the moving body 100 or stationary objects, which is not efficient.
  • the trajectory generation unit 206 sets a first area AR1 extending between the moving body 100 and the destination and a second area AR2 located outside the first area AR1, narrows down the objects for which risk is to be considered depending on whether each recognized object is located in the first area AR1 or the second area AR2, and generates a target trajectory TP based on the risk of the narrowed down objects.
  • FIG. 7 is a diagram showing an example of the first area AR1 and second area AR2 set by the trajectory generation unit 206 when generating a trajectory.
  • FIG. 7 shows, as an example, a case where the recognition unit 202 recognizes objects OB1 to OB4.
  • the trajectory generation unit 206 sets, for example, an area starting from the moving body 100 and ending at the destination (user U in FIG. 7) as the first area AR1, and sets an area expanded by a predetermined distance d based on the set first area AR1 as the second area AR2.
  • the trajectory generating unit 206 generates a target trajectory for an object that exists in the first area AR1 among the recognized objects, taking into account the risk value of the object, regardless of whether the object is stationary or moving, while generating a target trajectory for an object that exists in the second area AR2, taking into account the risk value of the object only when the object is moving.
  • the first area AR1 is set as an area starting from the moving body 100 and ending at the destination, and it is assumed that there is little need to take into account the risk value of an object that exists outside the first area AR1 when the object is stationary. Therefore, in the case of FIG.
  • the trajectory generating unit 206 takes into account the risk values of the moving object OB1 and stationary object OB2 in the first area AR1 and the risk value of the moving object OB3 in the second area AR2 (these objects are shown by diagonal lines in FIG. 7), while calculating the risk values of multiple trajectories without taking into account the risk value of the stationary object OB4 in the second area AR2, and adopts the trajectory with the smallest calculated risk value as the target trajectory TP.
  • Fig. 8 is a flowchart showing an example of the flow of processing executed by the control device 200.
  • the processing shown in Fig. 8 is executed when the mobile body 100 is traveling in a following mode, that is, when the user U itself is set as the destination, but even when the mobile body 100 is traveling in a guidance mode, the processing of this flowchart is executed in the same manner as long as the destination is recognized by the recognition unit 202.
  • the recognition unit 202 recognizes one or more objects in the vicinity of the moving body 100 and the user of the moving body 100, for example, based on an image captured by the camera 180 (step S100).
  • the risk distribution prediction unit 204 sets a risk for the one or more objects recognized by the recognition unit 202 (step S102).
  • the trajectory generation unit 206 sets a first area AR1 and a second area AR2 based on the positions of the recognized user and the moving body 100 (step S104).
  • the trajectory generation unit 206 then classifies the recognized object or objects into either the first area AR1 or the second area AR2 (step S106). Next, the trajectory generation unit 206 generates a target trajectory based on the risk of all objects contained in the first area AR1 and the risk of moving objects contained in the second area (step S108). Next, the drive control unit 208 controls the movement mechanism so that the moving body 100 moves along the generated target trajectory (step S110). This ends the processing of this flowchart.
  • the risk distribution prediction unit 204 sets a risk for the recognized objects, and then the trajectory generation unit 206 classifies the objects for which a risk has been set into a first area AR1 and a second area AR2.
  • the present invention is not limited to such a configuration, and the trajectory generation unit 206 may first classify the recognized objects into a first area AR1 and a second area AR2, and then the risk distribution prediction unit 204 may set a risk for all objects included in the first area AR1 and for moving objects included in the second area AR2.
  • the trajectory generation unit 206 generates multiple candidate trajectories and adopts the trajectory with the smallest risk value as the target trajectory, but the present invention is not limited to such a configuration, and the trajectory generation unit 206 may generate the target trajectory using any algorithm that generates a trajectory taking into account at least the risk value of the object.
  • the trajectory generation unit 206 sets the first area AR1 and the second area AR2 as rectangular areas, but the present invention is not limited to such a configuration, and the trajectory generation unit 206 may at least set the first area AR1 as a specified area from the moving body 100 to the destination, and set the second area AR2 as a different specified area that exists outside the first area AR1.
  • a target trajectory is generated depending on whether each of the recognized one or more objects is present in a first area extending between the moving body and the user, or in a second area located outside the first area. This makes it possible to efficiently generate a target trajectory for the robot.
  • a storage medium for storing computer-readable instructions
  • the processor executes the computer-readable instructions to: Recognizing one or more objects present around the moving body and a user of the moving body based on an image of a surrounding situation of the moving body; generating a target trajectory for following the user based on index values related to the recognized positions of the one or more objects; controlling a movement mechanism of the moving body so that the moving body moves along the target trajectory; A moving body that generates the target trajectory depending on whether each of the one or more recognized objects is located in a first area extending between the moving body and the user, or in a second area located outside the first area.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
PCT/JP2023/035663 2023-09-29 2023-09-29 移動体の制御装置、移動体の制御方法、およびプログラム Pending WO2025069386A1 (ja)

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JP2025548399A JPWO2025069386A1 (https=) 2023-09-29 2023-09-29
PCT/JP2023/035663 WO2025069386A1 (ja) 2023-09-29 2023-09-29 移動体の制御装置、移動体の制御方法、およびプログラム
CN202380101668.2A CN121729653A (zh) 2023-09-29 2023-09-29 移动体的控制装置、移动体的控制方法及程序

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH05297944A (ja) * 1992-04-24 1993-11-12 Fujitsu Ltd 移動ロボットの障害物回避方式
JP2008152599A (ja) * 2006-12-19 2008-07-03 Toyota Motor Corp 移動経路作成方法、自律移動体および自律移動体制御システム
WO2019031168A1 (ja) * 2017-08-07 2019-02-14 パナソニック株式会社 移動体および移動体の制御方法
WO2022138476A1 (ja) * 2020-12-23 2022-06-30 パナソニックＩｐマネジメント株式会社 ロボットの制御方法、ロボット、及びプログラム

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH05297944A (ja) * 1992-04-24 1993-11-12 Fujitsu Ltd 移動ロボットの障害物回避方式
JP2008152599A (ja) * 2006-12-19 2008-07-03 Toyota Motor Corp 移動経路作成方法、自律移動体および自律移動体制御システム
WO2019031168A1 (ja) * 2017-08-07 2019-02-14 パナソニック株式会社 移動体および移動体の制御方法
WO2022138476A1 (ja) * 2020-12-23 2022-06-30 パナソニックＩｐマネジメント株式会社 ロボットの制御方法、ロボット、及びプログラム

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