Control device, mobile body system, control method, and program

Abstract

This control device operates a mobile body by switching a mode between a delivery mode for moving to a destination and a remote operation mode in which a user remotely operates the mobile body. The control device comprises: an assessment unit that assesses whether or not the mobile body has arrived at the destination; a mode switching unit that if, while the mobile body is operating in the delivery mode, a condition is satisfied including the mobile body having arrived at the destination, switches an operation mode of the mobile body from the delivery mode to the remote operation mode; a generation unit that generates a target trajectory of the mobile body on the basis of the switched operation mode; and a control unit that controls the mobile body on the basis of the target trajectory.

Description

Control device, mobile system, control method, and program

[0001] The present invention relates to a control device, a mobile system, a control method, and a program.

[0002] Conventionally, a leading robot, which is an autonomous mobile body that leads a user in a supermarket, a shopping mall, etc., has been proposed (Patent Document 1). This leading robot generates a route to follow taking into account the surrounding congestion.

[0003] WO 2003 / 189105

[0004] However, while conventional mobile bodies such as lead robots have a lead mode in which they lead a user, they do not have a delivery mode in which they travel to a destination or a remote control mode in which a user remotely controls the mobile body. For this reason, conventional mobile bodies sometimes cannot switch between the delivery mode and the remote control mode to travel.

[0005] The present invention has been made in consideration of these circumstances, and one of its objects is to provide a control device, a mobile body system, a control method, and a program that can switch between delivery mode and remote control mode to allow a mobile body to travel.

[0006] The control device, mobile body system, control method, and program according to the present invention employ the following configuration: (1): A control device according to one aspect of the present invention operates a mobile body by switching between a delivery mode in which the mobile body travels to a destination and a remote operation mode in which a user remotely operates the mobile body, and includes: a determination unit that determines whether the mobile body has arrived at the destination; a mode switching unit that switches the operation mode of the mobile body from the delivery mode to the remote operation mode when a condition is met that includes the mobile body having arrived at the destination while the mobile body is operating in the delivery mode; a generation unit that generates a target trajectory of the mobile body based on the switched operation mode; and a control unit that controls the mobile body based on the target trajectory.

[0007] (2): In the above aspect (1), the mobile body further includes a work data acquisition unit that acquires work data from work equipment mounted on the mobile body, and a work data transmission unit that transmits the work data to an external information processing device using a communication device mounted on the mobile body.

[0008] (3): In the above aspect (2), a data abnormality determination unit is further provided that determines whether there is an abnormality in the work data, and the mode switching unit switches from the delivery mode to the remote control mode when conditions are met, including that the mobile body has arrived at the destination and that there is an abnormality in the work data.

[0009] (4): In the above aspect (1), a call detection unit is further provided that detects a call to the mobile body, and when a call to the mobile body is detected while the mobile body is operating in the delivery mode, the mode switching unit determines whether to switch to the remote control mode based on the content of the call.

[0010] (5) In the above aspect (4), the device further includes a response output unit that generates a response to the call and outputs the response when it is determined not to switch to the remote control mode.

[0011] (6): Another aspect of the mobile body system of the present invention is a mobile body system comprising a plurality of mobile bodies and a terminal device capable of communicating with the plurality of mobile bodies, wherein each of the plurality of mobile bodies is equipped with a control device described in any one of (1) to (5) above, and the terminal device selects one of the plurality of mobile bodies based on at least one of the type of work equipment mounted on each of the plurality of mobile bodies, the position of each of the plurality of mobile bodies, and the charging state of each of the plurality of mobile bodies.

[0012] (7): In another aspect of the control method of the present invention, a control device that operates a mobile body by switching between a delivery mode in which the mobile body travels to a destination and a remote control mode in which the user remotely controls the mobile body executes the following processes: determining whether the mobile body has arrived at the destination; switching the operation mode of the mobile body from the delivery mode to the remote control mode when a condition including the mobile body having arrived at the destination is met while the mobile body is operating in the delivery mode; generating a target trajectory for the mobile body based on the switched operation mode; and controlling the mobile body based on the target trajectory.

[0013] (8): A program according to another aspect of the present invention causes a processor of a control device that operates a mobile body by switching between a delivery mode in which the mobile body travels to a destination and a remote control mode in which the user remotely controls the mobile body to execute the following processes: determining whether the mobile body has arrived at the destination; switching the operation mode of the mobile body from the delivery mode to the remote control mode when a condition is met that includes the mobile body having arrived at the destination while the mobile body is operating in the delivery mode; generating a target trajectory for the mobile body based on the switched operation mode; and controlling the mobile body based on the target trajectory.

[0014] According to the aspects (1) to (8), the mobile object can be caused to travel by switching between a delivery mode and a remote control mode.

[0015] 1 is a diagram showing an example of the configuration of a mobile body system 1 including a mobile body 100. FIG. 2 is a perspective view showing the mobile body 100. FIG. 3 is a diagram showing the configuration of the mobile body 100 equipped with a control device 200. FIG. 4 is a diagram showing an example of the configuration of the control device 200. FIG. 5 is a diagram showing an example of a target trajectory generated by a generation unit 260. FIG. 6 is a diagram for explaining an environmental target risk function and an environmental target-based benefit function. X ｅ_ｌ 1 is a diagram illustrating an example of an environmental target risk function and an environmental target-based benefit function in an axial direction. ｅ_ｌ1 is a diagram showing an example of a potential function in an axial direction; FIG. 2 is an image diagram of an environmental target-based benefit function when environmental targets are detected at multiple detection positions; FIG. 3 is a diagram for explaining a traffic participant / obstacle risk function; FIG. 4 is a diagram for explaining a traffic participant / obstacle risk function based on traffic participant U2; X ｔｐ_ｌ 1 is a diagram illustrating an example of a traffic participant / obstacle risk function in the axial direction. ｔｐ_ｌ FIG. 1 is a diagram showing an example of a traffic participant / obstacle risk function in the axial direction. FIG. 2 is a diagram for explaining how the mobile body 100 is automatically traveling in delivery mode. FIG. 3 is a diagram for explaining how the user U1 gives an instruction to move the mobile body 100 to the left. FIG. 4 is a diagram showing an example of a remote control benefit function. FIG. 5 is a diagram for explaining how the direction of travel of the mobile body 100 is changed when a remote control benefit function is set. FIG. 6 is a diagram showing how the mobile body 100 travels to a hospital room where a patient is staying. FIG. 7 is a flowchart showing an example of processing executed by the control device 200.

[0016] Hereinafter, with reference to the drawings, embodiments of a control device, a mobile body system, a control method, and a program of the present invention will be described. The control device of the present invention controls the movement mechanism of a mobile body to move the mobile body. The mobile body of the present invention autonomously moves in an area where pedestrians walk. The area where pedestrians walk includes sidewalks, public open spaces, floors within buildings, etc., and may also include roadways. In the following description, it is assumed that no person rides in the mobile body, but it is acceptable for a person to ride in the mobile body. The mobile body operates in a delivery mode in which it travels to a destination, or in a remote control mode in which the user remotely controls the mobile body.

[0017] [Mobile System] FIG. 1 is a diagram illustrating an example of the configuration of a mobile system 1 including a mobile object 100. The mobile object system 1 includes, for example, the mobile object 100, a user terminal device 300, and a nurse station 400. These communicate with each other via, for example, a network NW. The network NW may be any network such as a LAN, a WAN, or an internet connection. Note that the mobile object 100, the user terminal device 300, and the nurse station 400 may communicate directly via short-range wireless communication without using the network NW. In the following description, it is assumed that the mobile object 100 travels within a hospital, and that the nurse station 400 is located within the hospital. The nurse station 400 is equipped with a computer and is capable of communicating with the mobile object 100.

[0018] [User Terminal Device] The user terminal device 300 is, for example, a computer that remotely controls the mobile object 100 and inputs a destination in delivery mode based on the operation of the user U1. The user terminal device 300 may be equipped with an input unit such as a keyboard, mouse, or touch panel that allows the user to input a destination in delivery mode. The user terminal device 300 is located in a remote location separate from the nurse station 400.

[0019] The user terminal device 300 may include an input device such as a joystick. For example, the user U1 may operate the joystick to control the direction of travel of the moving object 100. Specifically, the user U1 can instruct the moving object 100 to move leftward relative to the direction of travel by tilting the joystick to the left. Furthermore, the user U1 can instruct the moving object 100 to move rightward relative to the direction of travel by tilting the joystick to the right.

[0020] The user terminal device 300 transmits operation information based on the operation of the user U1 to the moving body 100. The joystick may be provided with a start button for instructing the moving body 100 to start moving and a stop button for instructing the moving body 100 to stop moving.

[0021] The user terminal device 300 transmits operation information output from an input device such as a joystick to the mobile object 100 via the network NW. The user terminal device 300 also transmits destination information indicating a destination in delivery mode input by the user to the mobile object 100 via the network NW.

[0022] The user terminal device 300 also receives image information transmitted from the mobile object 100. The image information is an image captured by a camera installed on the mobile object 100. The user terminal device 300 may be equipped with a display unit such as a liquid crystal display or an organic EL display. The user terminal device 300 may display the image information received from the mobile object 100 on the display unit. The user U1 operates an input device such as a joystick based on the image of the area around the mobile object 100 displayed on the display unit 330.

[0023] The user U1 may control the angle of view of the camera of the moving body 100 via the user terminal device 300. For example, the user U1 may control the pan, tilt, and zoom of the camera provided on the moving body 100 by operating the user terminal device 300. The user terminal device 300 may also be a wearable device such as VR goggles. In this case, the user may control the camera in accordance with the movement of the VR goggles.

[0024] The user terminal device 300 may be, for example, a portable terminal device such as a smartphone or tablet device operated by the user U1. In this case, the user terminal device 300 may be equipped with a touch panel and may accept instructions from the user U1 input using the touch panel. The user terminal device 300 may also be equipped with a voice recognition function and may accept instructions based on the voice of the user U1 recognized using the voice recognition function.

[0025] 2 is a perspective view showing the mobile body 100. The mobile body 100 includes, for example, a base body 10, a door unit 60 provided on the base body 10, and wheels (first wheel 20, second wheel 30, and third wheel 40) attached to the base body 10. For example, a user U1 can open the door unit 60 to put luggage into a storage compartment provided on the base body 10 or take luggage out of the storage compartment. The first wheel 20 and the second wheel 30 are driving wheels, and the third wheel 40 is an auxiliary wheel (driven wheel).

[0026] A cylindrical support body 50 extending upward is provided on the upper surface of the base body 10. A camera 80 that captures images of the surroundings of the moving body 100 is provided at the end of the support body 50. The position at which the camera 80 is provided may be any position different from the above.

[0027] The camera 80 is, for example, a camera that can capture images of the periphery of the moving body 100 at a wide angle (for example, 360 degrees). The camera 80 may include multiple cameras. For example, the camera 80 may be realized by combining multiple 120-degree cameras or multiple 60-degree cameras.

[0028] 3 is a diagram showing the configuration of a mobile body 100 equipped with a control device 200. The mobile body 100 includes, for example, an HMI 110, a detection device 120, a position identification device 130, a communication device 170, a work facility 180, a base 160 on which the control device 200 is mounted, a moving mechanism 140 attached to the base 160, and a sensor 150 attached to the moving mechanism 140, etc. The base 160 may be the same as the base 10 in FIG.

[0029] The HMI 110 presents various information to the user U1 and accepts input operations by the user U1. The HMI 110 includes various display devices, a speaker, a microphone, a buzzer, a touch panel, switches, keys, and the like.

[0030] The detection device 120 is a device that generates data for recognizing objects present around the mobile body 100. The detection device 120 includes, for example, an object recognition device that recognizes objects based on the output of the camera 80. Note that the detection device 120 may recognize objects by using sensors such as a radar device, a LIDAR (Light Detection and Ranging), and an ultrasonic sensor in addition to the camera 80, and by performing sensor fusion processing based on the outputs of these sensors.

[0031] The positioning device 130 is a device that determines the position of the mobile body 100. The positioning device 130 includes, for example, a Global Navigation Satellite System (GNSS) receiver that determines the position of the mobile body 100 based on signals received from GNSS satellites. The positioning device 130 may determine or supplement the position of the mobile body 100 using an Inertial Navigation System (INS) that uses the output of a sensor 150, which will be described later. The positioning device 130 may also have an electromagnetic wave receiving function and determine or supplement the position of the mobile body 100 based on the intensity of electromagnetic waves arriving from surrounding electromagnetic wave sources (whose positions are known).

[0032] The movement mechanism 140 is a mechanism for moving the moving body 100 in any direction. The movement mechanism 140 includes, for example, a plurality of wheels (first wheel 20, second wheel 30, and third wheel 40), a drive motor attached to one or more of the wheels, and a steering device attached to one or more of the wheels. There are no particular restrictions on the configuration of the movement mechanism 140, and the movement mechanism 140 may include components other than wheels, such as pseudo feet for bipedal walking or caterpillars.

[0033] The sensor 150 is a sensor for detecting the behavior of the mobile body 100. The sensor 150 includes, for example, a wheel speed sensor for detecting the speed of the wheels, an acceleration sensor for detecting the acceleration acting on the mobile body 100, a yaw rate sensor attached near the center of gravity of the base body 160 in the horizontal direction, a steering angle sensor for detecting the steering angle of the steered wheels (steered wheels), and an orientation sensor for detecting the orientation of the mobile body 100 in the horizontal direction.

[0034] The communication device 170 is a wireless communication module that performs wireless communication with a wireless base station connected to the network NW. The communication device 170 communicates with the user terminal device 300 via the network NW. The communication device 170 may also directly communicate with the user terminal device 300 by short-range wireless communication.

[0035] The work equipment 180 is equipment that outputs work data. For example, if the mobile object 100 is used in a hospital, the work equipment 180 may be a body temperature measuring device or a blood pressure measuring device. In this case, the work equipment 180 may output body temperature data or blood pressure data measured from a patient as work data. The work equipment 180 is not limited to these, and may be any equipment that outputs work data when a person performs work.

[0036] FIG. 4 illustrates an exemplary configuration of the control device 200. The control device 200 includes, for example, a first detection unit 210, a first determination unit 220, a second detection unit 230, a second determination unit 240, a calculation unit 250, a generation unit 260, a control unit 270, a determination unit 280, a mode switching unit 282, a work data acquisition unit 284, a work data transmission unit 286, a data abnormality determination unit 288, a call detection unit 290, and a response output unit 292. These components are implemented by a hardware processor, such as a central processing unit (CPU), executing a program (software). Some or all of these components may be implemented by hardware (including circuitry), such as a large-scale integration (LSI), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a graphics processing unit (GPU), or may be implemented by a combination of software and hardware. The program may be stored in advance in a storage device (a storage device with a non-transitory storage medium) such as a hard disk drive (HDD) or flash memory, or may be stored in a removable storage medium (a non-transitory storage medium) such as a DVD or CD-ROM, and installed in the storage device by inserting the storage medium into a drive device. Note that the control device 200 may store map information including at least a local map of the location where the mobile object 100 operates in the storage device.

[0037] The first detection unit 210 detects the location of the destination in the delivery mode based on the destination information received by the communication device 170 from the user terminal device 300. The first detection unit 210 also detects an operation performed by the user U1 on the mobile object 100 based on operation information received by the communication device 170 from the user terminal device 300.

[0038] The second detection unit 230 detects the position of an interfering object around the mobile body 100 that the mobile body 100 should avoid, based on information input from the detection device 120. An interfering object is an object that interferes with the traveling of the mobile body 100. For example, the interfering object is an environmental object, a traffic participant, an obstacle, or other object around the mobile body 100 that the mobile body 100 should avoid. An environmental object is, for example, an object at the boundary of the traveling lane that the mobile body 100 cannot enter, such as a wall or a lawn. A traffic participant is, for example, a pedestrian or a vehicle. An obstacle is, for example, a stationary object on the traveling lane that obstructs the traveling of the mobile body 100. The mobile body 100 repeatedly detects the position of the interfering object at predetermined time intervals to avoid contact with the interfering object while traveling.

[0039] The first determination unit 220 determines a remote control benefit function indicating the degree to which it is recommended to drive the mobile object 100, based on the operation of the user U1 on the mobile object 100 detected by the first detection unit 210. The first determination unit 220 also determines an environmental target-based benefit function based on the position of the destination in the delivery mode detected by the first detection unit 210 and the positions of environmental targets detected by the second detection unit 230. The remote control benefit function and the environmental target-based benefit function will be described in detail later.

[0040] The second determination unit 240 determines a risk function indicating the degree of risk of interference between the mobile body 100 and the interfering object, based on the position of the interfering object detected by the second detection unit 230. Specifically, the second determination unit 240 determines the environmental object risk function based on the position of the environmental object detected by the second detection unit 230. The second determination unit 240 also determines a traffic participant / obstacle risk function based on the positions of the traffic participants and obstacles detected by the second detection unit 230. The environmental object risk function and the traffic participant / obstacle risk function will be described in detail later.

[0041] The calculation unit 250 calculates an evaluation function for evaluating the route along which the mobile object 100 will travel, based on the remote control benefit function and the environmental landmark-based benefit function determined by the first determination unit 220, and the environmental landmark risk function and the traffic participant / obstacle risk function determined by the second determination unit 240. Details of the evaluation function will be described later.

[0042] The generation unit 260 generates a target trajectory for the moving body 100 based on the evaluation function calculated by the calculation unit 250. For example, the generation unit 260 generates the target trajectory for the moving body 100 using a model that represents a portion of the periphery of a geometric shape. The model may be an arc model that represents an arc. The generation unit 260 generates the target trajectory for the moving body 100 by modeling the trajectory of the moving body 100 using the arc model. The generation process of the target trajectory by the generation unit 260 will be described below.

[0043] [Process for generating target trajectory] Fig. 5 is a diagram showing an example of a target trajectory generated by the generation unit 260. As shown in Fig. 5, the generation unit 260 generates a target trajectory for the moving body 100 by combining first to third predicted trajectories, which are arc-shaped.

[0044] 5, an XY coordinate system is defined with the center of the current position of the moving body 100 as the origin, the X axis in front of the moving body 100 as the front, and the Y axis to the left of the moving body 100 as the left.

[0045] Then, the position after the first predicted time from the origin in this XY coordinate system is defined as the first predicted position Z ｍ１ and the first predicted position Z ｍ１ The trajectory up to is defined as a first predicted trajectory in the form of an arc.

[0046] The radius of curvature of the first predicted trajectory is R ｍ１ The rotation angle of the first predicted trajectory is θ ｍ１ The rotation angle θ ｍ１ corresponds to the angle between the Y axis and the Y' axis, which will be described later.

[0047] Also, the first predicted position Z ｍ１ The predicted position when the trajectory is divided into three equal parts is calculated by dividing the trajectory from the origin to the first predicted position Zｍ１ , three predicted positions Z ｍ１１ , Z ｍ１２ , Z ｍ１３ (=Z ｍ１ )

[0048] Next, the second predicted trajectory will be described. ｍ１ (= predicted position Z ｍ１３ ) is the origin, and the first predicted position Z ｍ１ An X'-Y' coordinate system is defined in which the tangent direction at is the X' axis and the direction perpendicular to this tangent line is the Y' axis.

[0049] Then, the origin of this X'-Y' coordinate system (i.e., the first predicted position Z ｍ１ ) and the position after the second predicted time is set as the second predicted position Z ｍ２ and the first predicted position Z ｍ１ to the second predicted position Z ｍ２ The trajectory up to is defined as a second predicted trajectory in the form of an arc.

[0050] The radius of curvature of the second predicted orbit is R ｍ２ The rotation angle of the second predicted orbit is θ ｍ２ The rotation angle θ ｍ２ corresponds to the angle between the Y′ axis and the Y″ axis described below.

[0051] Next, the third predicted trajectory will be described. ｍ２ is set as the origin, and the second predicted position Z ｍ２ An X''-Y'' coordinate system is defined in which the tangent direction at is the X'' axis and the direction perpendicular to this tangent line is the Y'' axis.

[0052] The origin of this X'-Y' coordinate system (i.e., the second predicted position Z ｍ２ ) and the position after the third predicted time is the third predicted position Z ｍ３ and the second predicted position Z ｍ２ to the third predicted position Z ｍ３ The trajectory up to is defined as a third predicted trajectory in the form of an arc.

[0053] As described above, the first predicted orbit is determined as a combination of three predicted orbits that are shorter than the second and third predicted orbits. ｍ１１ The trajectory to and predicted position Z ｍ１１ From predicted position Z ｍ１２ The trajectory to and predicted position Z ｍ１２ From predicted position Z ｍ１３ The first predicted trajectory is determined as a combination of the trajectories up to

[0054] This is because the first predicted trajectory is closer to the moving body 100 than the second predicted trajectory and the third predicted trajectory, and therefore it is necessary to generate a predicted trajectory that can more reliably avoid interference with an interfering object. Note that the generation unit 260 may determine the first predicted trajectory as a combination of two or four or more predicted trajectories.

[0055] The generator 260 calculates the rotation angle θ ｍ１ ~θ ｍ３ and the radius of curvature R ｍ１ ~R ｍ３ A plurality of trajectories are generated by determining a combination of a plurality of patterns of the above. Then, the generation unit 260 evaluates each of the generated plurality of trajectories using the evaluation function calculated by the calculation unit 250. Thereafter, the generation unit 260 determines one of the generated plurality of trajectories as a target trajectory for the moving body 100 based on the evaluation result using the evaluation function. By evaluating the generated plurality of trajectories based on the evaluation function, the generation unit 260 can generate a target trajectory for the moving body 100 that has a low risk of interfering with an interfering object and is suitable for the following mode or the leading mode. Details of the evaluation process using the evaluation function will be described later.

[0056] Returning to the explanation of Fig. 4, the control unit 270 controls the movement mechanism 140 so that the moving body 100 moves along the target trajectory generated by the generation unit 260. The control unit 270 controls the drive motor and steering device so that the position and behavior of the moving body 100 obtained from the output of the sensor 150 approach the target trajectory.

[0057] The determination unit 280 determines whether the mobile object 100 has arrived at the destination. For example, the determination unit 280 may determine that the mobile object 100 has arrived at the destination when the current location of the mobile object 100 identified by the position identification device 130 is within a predetermined distance from the location of the destination detected by the first detection unit 210.

[0058] The mode switching unit 282 switches the operation mode (e.g., delivery mode and remote control mode) of the mobile object 100. For example, when the mobile object 100 is operating in the delivery mode and a condition is met, including that the mobile object 100 has arrived at its destination, the mode switching unit 282 switches the operation mode of the mobile object 100 from the delivery mode to the remote control mode. Details of this mode switching will be described later.

[0059] The work data acquisition unit 284 acquires work data from the work equipment 180 mounted on the mobile body 100. For example, if the work equipment 180 is a body temperature measuring device or a blood pressure measuring device, the work data acquisition unit 284 acquires body temperature data or blood pressure data from the work equipment 180 as work data.

[0060] The work data transmission unit 286 transmits the work data to an external information processing device using the communication device 170 mounted on the mobile object 100. For example, the external information processing device may be a server that manages data on hospitalized patients. In this case, the work data transmission unit 286 may transmit body temperature data and blood pressure data as work data to the external information processing device.

[0061] The data anomaly determination unit 288 determines whether or not there is an anomaly in the work data. For example, the data anomaly determination unit 288 may determine that there is an anomaly in the work data if the value indicated by the work data is not within a predetermined range. For example, if the work data is patient body temperature data, the data anomaly determination unit 288 may determine that there is an anomaly in the work data if the patient's body temperature indicated by the body temperature data is not within a predetermined range (e.g., 36.0°C or higher and less than 37.0°C). Furthermore, if the work data is patient blood pressure data, the data anomaly determination unit 288 may determine that there is an anomaly in the work data if the patient's blood pressure indicated by the blood pressure data is not within a predetermined range (e.g., less than 140 / 90 mmHg).

[0062] The call detection unit 290 detects a call to the mobile object 100. For example, the call detection unit 290 may detect a call to the mobile object 100 using a microphone provided in the HMI 110. Specifically, the call detection unit 290 may detect a call to the mobile object 100 by recognizing, using a voice recognition function, a sound around the mobile object 100 detected using the microphone.

[0063] The response output unit 292 generates a response to the call detected by the call detection unit 290 and outputs the response. For example, the response output unit 292 may automatically generate a response to a greeting or a response to simple conversation and output the response from a speaker provided in the HMI 110. The response output unit 292 may generate the response using a learning model generated in advance by machine learning conversational exchanges.

[0064] [Environmental Target Risk Function and Environmental Target-Based Benefit Function] Next, the environmental target risk function and the environmental target-based benefit function will be described. The environmental target risk function is a function that indicates the degree of risk of interference between the mobile object 100 and an environmental target (e.g., a wall, a lawn, etc.). Conversely, the environmental target-based benefit function is a function that indicates the degree of non-interference between the mobile object 100 and an environmental target.

[0065] 6 is a diagram for explaining the environmental target risk function and the environmental target-based benefit function. As shown in FIG. 6, the traveling direction of the mobile object 100 is the Y axis, and the direction perpendicular to the Y axis is the X axis. Since there are multiple environmental targets R1 to R3 around the mobile object 100, the mobile object 100 needs to travel in a manner that does not interfere with these multiple environmental targets R1 to R3.

[0066] In the example shown in Fig. 6, the second detection unit 230 detects the position of the environmental target R2 based on information input from the detection device 120. Here, the detected position of the environmental target R2 is designated as E_l. In Fig. 6, only one detected position E_l is shown, but in reality, the environmental target R2 is detected at multiple locations.

[0067] In the XY coordinate system defined by the X and Y axes, the coordinates of the detected position E_l are defined as (xe_l, ye_l), where the subscript l represents the number of the detected environmental object, and l=1, 2, ..., n. ｅ Let us say that ｅ represents the total number of detected positions of environmental targets.

[0068] Furthermore, the direction from the center of the moving body 100 toward the detection position E_l is defined as X ｅ_ｌ axis, X ｅ_ｌ The direction perpendicular to the axis is Y ｅ_ｌ The X axis and the X ｅ_ｌ The angle between the axis and the ｅ_ｌ Then, ψ ｅ_ｌ is expressed as the following equation (1).

[0069] ψ ｅ_ｌ =tan －１ (ye_l / xe_l) …(1)

[0070] Furthermore, the coordinates in the XY coordinate system of the predicted position on the trajectory generated by the generation unit 260 are expressed as Z ｍｊ (X ｍｊ , Y ｍｊ The subscript j represents the number of the predicted position on the trajectory generated by the generator 260, where j=1, 2, ..., n ｍ Let us say that ｍrepresents the total number of predicted positions on the trajectory generated by the generation unit 260. In the example shown in FIG. 5, five predicted positions (Z ｍ１１ , Z ｍ１２ , Z ｍ１３ (=Z ｍ１ ), Z ｍ２ , Z ｍ３ ) is obtained, so n ｍ =5.

[0071] Furthermore, the coordinate Z of the predicted position is calculated based on the following equations (2) and (3): ｍｊ (X ｍｊ , Y ｍｊ ) to X ｅ_ｌ Axis and Y ｅ_ｌ X axis defined by ｅ_ｌ -Y ｅ_ｌ Coordinate Z in the coordinate system ｍｊ_ｅｌ (X ｍｊ_ｅｌ , Y ｍｊ_ｅｌ ) to

[0072] X ｍｊ_ｅｌ = (X ｍｊ -xe_l) cos ψ ｅ_ｌ + (Y ｍｊ -ye_l) sinψ ｅ_ｌ …(2)

[0073] Y ｍｊ_ｅｌ =-(X ｍｊ -xe_l) sinψ ｅ_ｌ + (Y ｍｊ -ye_l) cos ψ ｅ_ｌ …(3)

[0074] FIG. 7 shows the X ｅ_ｌ 7 is a diagram showing an example of an environmental target risk function and an environmental target-based benefit function in the axial direction. As shown in FIG. 7, the first determination unit 220 defines the environmental target-based benefit function Pe_x_b with the detection position E_l of the environmental target R2 as the origin. Also, the second determination unit 240 defines the environmental target-based benefit function Pe_x_b with the detection position E_l of the environmental target R2 as the origin. ｅ_ｌ Define the environmental target risk function Pe_x_r in the axial direction.

[0075] The second determination unit 240 determines X so that it has a gradient in the first sign direction (positive direction). ｅ_ｌ The first determination unit 220 defines an environmental target risk function Pe_x_r in the axial direction, and defines an environmental target-based benefit function Pe_x_b to have a gradient in a second sign direction (negative direction) opposite to the first sign direction (positive direction).

[0076] As shown in FIG. ｅ_ｌ The environmental target risk function Pe_x_r in the axial direction is ｅ_ｌ The larger the coordinate value on the X axis, the larger the risk function value. ｅ_ｌ The axis value is set only in the positive area. ｅ_ｌ The environmental target-based benefit function Pe_x_b in the axial direction is ｅ_ｌ The smaller the coordinate value of the X axis, the smaller the benefit function value. ｅ_ｌ The axis values ​​are set only in the negative range. Note that the larger the risk function value, the higher the risk of the moving object 100 interfering with the interfering object, and the smaller the benefit function value, the lower the risk of the moving object 100 interfering with the interfering object.

[0077] FIG. ｅ_ｌ 8 is a diagram illustrating an example of a potential function in the axial direction. As shown in FIG. 8, the potential function Pe_y is a function whose origin is the detected position E_l of the environmental object R2. The second determination unit 240 determines the potential function Pe_y by ｅ_ｌ It is defined as the environmental target risk function in the axial direction.

[0078] Y ｅ_ｌ The environmental target risk function (potential function Pe_y) in the axial direction is expressed as Y ｅ_ｌ The closer the coordinate of the axis is to 0, the larger the risk function value becomes. As shown in FIGS. 7 and 8, ｅ_ｌ The environmental target risk function Pe_x_r in the axial direction and Y ｅ_ｌ The environmental target risk function Pe_y in the axial direction has a different shape from the environmental target risk function Pe_y in the axial direction. ｅ_ｌ The environmental target risk function Pe_x_r in the axial direction is defined as X ｅ_ｌBy defining the risk function value so that it increases as the coordinate value of the axis increases, it is possible to prevent the target trajectory of the moving body 100 from being generated toward a position beyond the environmental target. ｅ_ｌ The environmental target risk function Pe_y in the axial direction is also expressed as X ｅ_ｌ If it is defined as a function similar to the environmental target risk function Pe_x_r in the axial direction, the calculation load on the control device 200 will increase. ｅ_ｌ The environmental object risk function Pe_y in the axial direction is defined so that the position of the origin (i.e., the position where the environmental object R2 is detected) is at its peak.

[0079] Next, a method for calculating the environmental target risk function value will be described. As described above, the coordinate Z of the predicted position on the predicted trajectory in the XY coordinate system is ｍｊ (X ｍｊ , Y ｍｊ ) is X ｅ_ｌ -Y ｅ_ｌ Coordinate Z of the predicted position in the coordinate system ｍｊ_ｅｌ (X ｍｊ_ｅｌ , Y ｍｊ_ｅｌ At the current time k, the X coordinate of the predicted position X ｍｊ_ｅｌ The risk function value based on the above is Pe_x_r_j_l(k), and the Y coordinate of the predicted position Y ｍｊ_ｅｌ The risk function value based on this is defined as Pe_y_j_l(k). Pe_x_r_j_l(k) can be found from Pe_x_r shown in Fig. 7. Pe_y_j_l(k) can be found from Pe_y shown in Fig. 8.

[0080] In this case, the risk function value Pe_r_j_l(k) for each detection position on the environmental target can be expressed as in equation (4). That is, Pe_r_j_l(k) can be obtained by multiplying Pe_x_r_j_l(k) and Pe_y_j_l(k).

[0081] Pe_r_j_l(k)=Pe_x_r_j_l(k)×Pe_y_j_l(k)...(4)

[0082] Furthermore, the total risk function value Pe_r_j(k) for the coordinates of the predicted position on the predicted trajectory can be expressed as in equation (5). That is, the risk function values ​​Pe_r_j_l(k) (l=1, 2, ..., n) for all detected positions on the environmental targets can be expressed as ｅ ) can be used to find Pe_r_j(k).

[0083] Pe_r_j(k) = Σ ｌ＝１ ｎｅ (Pe_r_j_l(k)) …(5)

[0084] The environmental target risk function value Pe_r(k) can be expressed as in equation (6). That is, the total risk function value Pe_r_j(k) (j=1, 2, ..., n) for the coordinates of all predicted positions on the predicted trajectory is ｍ ) can be summed to obtain the environmental target risk function value Pe_r(k).

[0085] Pe_r(k) = Σ ｊ＝１ ｎｍ (Pe_r_j(k)) …(6)

[0086] Next, a method for calculating the environmental target-based benefit function value will be described. As described in FIG. 7, the first determination unit 220 defines the environmental target-based benefit function Pe_x_b with the detected position E_l of the environmental target R2 as the origin. In addition, the first determination unit 220 calculates the potential function Pe_y shown in FIG. 8 by multiplying Y ｅ_ｌ It is defined as the environmental target-based benefit function in the axial direction.

[0087] As mentioned above, the coordinate Z of the predicted position on the predicted trajectory in the XY coordinate system ｍｊ (X ｍｊ , Y ｍｊ ) is X ｅ_ｌ -Y ｅ_ｌ Coordinate Z of the predicted position in the coordinate system ｍｊ_ｅｌ (X ｍｊ_ｅｌ , Y ｍｊ_ｅｌ At the current time k, the X coordinate of the predicted position X ｍｊ_ｅｌ The benefit function value based on the above is Pe_x_b_j_l(k), and the Y coordinate of the predicted position Y ｍｊ_ｅｌThe benefit function value based on the above is defined as Pe_y_j_l(k). Pe_x_b_j_l(k) can be found from Pe_x_b shown in Fig. 7. Pe_y_j_l(k) can be found from Pe_y shown in Fig. 8.

[0088] In this case, the benefit function value Pe_b_j_l(k) for each detection position on the environmental object can be expressed as in equation (7). That is, Pe_b_j_l(k) can be obtained by multiplying Pe_x_b_j_l(k) and Pe_y_j_l(k).

[0089] Pe_b_j_l(k)=Pe_x_b_j_l(k)×Pe_y_j_l(k)...(7)

[0090] Furthermore, the total benefit function value Pe_b_j(k) for the coordinates of the predicted position on the predicted trajectory can be expressed as in equation (8). That is, the benefit function values ​​Pe_b_j_l(k) (l=1, 2, ..., n) for all detected positions on the environmental targets can be expressed as ｅ ) can be obtained as Pe_b_j(k).

[0091] Pe_b_j(k)=max Pe_b_j_l(k) =max Pe_x_b_j_l(k)×Pe_y_j_l(k)...(8)

[0092] 9 is an image diagram of the environmental target-based benefit function when environmental targets are detected at multiple detection positions. As shown in Fig. 9, for example, assume that there are walls on both the left and right sides, and environmental targets are detected on the right and left sides of the traveling direction of the mobile body 100. Furthermore, the environmental target-based benefit function set based on the detection position on the left side of the traveling direction of the mobile body 100 is denoted as Pe_x_b_1, and the environmental target-based benefit function set based on the detection position on the right side of the traveling direction of the mobile body 100 is denoted as Pe_x_b_2.

[0093] In this case, the first determination unit 220 determines the maximum value of the multiple benefit function values ​​(Pe_x_b_1 and Pe_x_b_2) as X ｅ_ｌ The environmental target-based benefit function value in the axial direction is set as Pe_b_j(k). The maximum value is selected because the benefit function should be set taking into consideration the balance with all environmental targets. For this reason, in the above-mentioned equation (8), Pe_b_j(k) is calculated taking into consideration the maximum value.

[0094] The environmental object-based benefit function value Pe_b(k) can be expressed as in equation (9). That is, the total benefit function value Pe_b_j(k) (j=1, 2, ..., n) for the coordinates of all predicted positions on the predicted trajectory is ｍ ) to obtain the environmental object-based benefit function value Pe_b(k).

[0095] Pe_b(k) = Σ ｊ＝１ ｎｍ (Pe_b_j(k)) …(9)

[0096] [Traffic Participant / Obstacle Risk Function] Next, the traffic participant / obstacle risk function will be described. The traffic participant / obstacle risk function is a function that indicates the degree of risk of interference between the mobile object 100 and a traffic participant or an obstacle.

[0097] 10 is a diagram for explaining the traffic participant / obstacle risk function. As shown in FIG. 10, the traveling direction of the mobile object 100 is the Y axis, and the direction perpendicular to the Y axis is the X axis. Since multiple traffic participants U2 and U3 exist around the mobile object 100, the mobile object 100 needs to travel in a manner that does not interfere with these multiple traffic participants U2 and U3.

[0098] 10 , the second detection unit 230 detects the positions of traffic participants U2 and U3 based on information input from the detection device 120. In addition, the second determination unit 240 sets a traffic participant / obstacle risk function to the positions of traffic participants U2 and U3 detected by the second detection unit 230.

[0099] FIG. 11 is a diagram for explaining the traffic participant / obstacle risk function based on the traffic participant U2. The following describes the process of determining the traffic participant / obstacle risk function based on the traffic participant U2 by the second determination unit 240. In FIG. 11, the detected position of the traffic participant U2 is designated as TP_l. Although FIG. 11 only shows the detected position TP_l of the traffic participant U2, in reality, the traffic participant U3 is also detected. Note that if there are obstacles on the road in addition to the traffic participants, the second detection unit 230 will also detect the obstacles.

[0100] In the XY coordinate system defined by the X and Y axes, the coordinates of the detected position TP_l are defined as (xtp_l, ytp_l), where the subscript l represents the number of the detected position of the traffic participant / obstacle, and l = 1, 2, ..., n. ｔ Let us say that ｔ represents the total number of detected positions of traffic participants and obstacles. The traveling direction of traffic participant U2 is the Ytp_l axis, and the direction perpendicular to the Ytp_l axis is the Xtp_l axis.

[0101] Furthermore, the coordinates in the XY coordinate system of the predicted position on the trajectory generated by the generation unit 260 are expressed as Z ｍｊ (X ｍｊ , Y ｍｊ ) is defined as follows. Using the same method as in the above equations (2) and (3), the coordinate Z of the predicted position is calculated. ｍｊ (X ｍｊ , Y ｍｊ ) is X ｔｐ_ｌ Axis and Y ｔｐ_ｌ X axis defined by ｔｐ_ｌ -Y ｔｐ_ｌ Coordinate Z in the coordinate system ｍｊ_ｔｐｌ (X ｍｊ_ｔｐｌ , Y ｍｊ_ｔｐｌ ) is converted to

[0102] FIG. 12 shows the X ｔｐ_ｌ 12 is a diagram illustrating an example of a traffic participant / obstacle risk function in the axial direction. As shown in FIG. 12, the second determination unit 240 determines the detected position TP_l of the traffic participant U2 as the origin, and calculates the X ｔｐ_ｌThe traffic participant / obstacle risk function Ptp_x in the axial direction is defined. The second determination unit 240 determines X so that it has a gradient in the first sign direction (positive direction). ｔｐ_ｌ Define a traffic participant / obstacle risk function Ptp_x in the axial direction.

[0103] As shown in FIG. ｔｐ_ｌ The risk function Ptp_x for traffic participants and obstacles in the axial direction is ｔｐ_ｌ The closer the axis coordinate is to 0, the larger the risk function value becomes.

[0104] FIG. 13 shows the Y ｔｐ_ｌ 13 is a diagram illustrating an example of a traffic participant / obstacle risk function in the axial direction. As shown in FIG. 13, the second determination unit 240 determines the detected position TP_l of the traffic participant U2 as the origin, and calculates the Y ｔｐ_ｌ The traffic participant / obstacle risk function Ptp_y in the axial direction is defined. The second determination unit 240 determines Y so that it has a gradient in the first sign direction (positive direction). ｔｐ_ｌ Define a traffic participant / obstacle risk function Ptp_y in the axial direction.

[0105] As shown in FIG. ｔｐ_ｌ The risk function Ptp_y for traffic participants and obstacles in the axial direction is ｔｐ_ｌ The closer the axis coordinate is to 0, the larger the risk function value becomes.

[0106] Next, we will explain how to calculate the traffic participant / obstacle risk function value. As mentioned above, the coordinate Z of the predicted position on the predicted trajectory in the XY coordinate system is ｍｊ (X ｍｊ , Y ｍｊ ) is X ｔｐ_ｌ -Y ｔｐ_ｌ Coordinate Z of the predicted position in the coordinate system ｍｊ_ｔｐｌ (X ｍｊ_ｔｐｌ , Y ｍｊ_ｔｐｌ At the current time k, the X coordinate of the predicted position X ｍｊ_ｔｐｌ The risk function value based on the above is Ptp_x_j_l(k), and the Y coordinate of the predicted position is Y ｍｊ_ｔｐｌThe risk function value based on this is defined as Ptp_y_j_l(k). Ptp_x_j_l(k) can be found from Ptp_x shown in Fig. 12. Ptp_y_j_l(k) can be found from Ptp_y shown in Fig. 13.

[0107] In this case, the risk function value Ptp_r_j_l(k) for each detected position of a traffic participant / obstacle can be expressed as in equation (10). That is, Ptp_r_j_l(k) can be obtained by multiplying Ptp_x_j_l(k) and Ptp_y_j_l(k).

[0108] Ptp_r_j_l(k)=Ptp_x_j_l(k)×Ptp_y_j_l(k)...(10)

[0109] The total risk function value Ptp_r_j(k) for the coordinates of the predicted position on the predicted trajectory can be expressed as in equation (11). That is, the risk function values ​​Ptp_r_j_l(k) (l=1, 2, ..., n) for all detected positions of traffic participants and obstacles can be expressed as ｔ ) can be used to find Ptp_r_j(k).

[0110] Ptp_r_j(k)=Σ ｌ＝１ ｎｔ (Ptp_r_j_l(k)) …(11)

[0111] The traffic participant / obstacle risk function value Ptp_r(k) can be expressed as in equation (12). That is, the total risk function value Ptp_r_j(k) (j=1, 2, ..., n) for the coordinates of all predicted positions on the predicted trajectory is ｍ ) can be used to calculate the traffic participant / obstacle risk function value Ptp_r(k).

[0112] Ptp_r(k) = Σ ｊ＝１ ｎｍ (Ptp_r_j(k)) …(12)

[0113] [Remote Operation Benefit Function] Next, the remote operation benefit function will be described. The remote operation benefit function is a function that indicates the degree to which it is recommended to drive the mobile body 100, and is determined based on the operation of the mobile body 100 by the user U1. The remote operation benefit function is also a function that is set in the remote operation mode or the delivery mode.

[0114] 14 is a diagram illustrating the state in which the mobile object 100 is automatically traveling in delivery mode. As shown in FIG. 14, the direction of travel of the mobile object 100 is the Y axis, and the direction perpendicular to the Y axis is the X axis. Since there are multiple environmental landmarks R4 to R6 and a traffic participant U4 (hereinafter referred to as pedestrian U4) around the mobile object 100, the mobile object 100 must travel in a manner that does not interfere with these multiple environmental landmarks R4 to R6 and pedestrian U4.

[0115] When the operation mode of the mobile object 100 is switched to the delivery mode by the mode switching unit 282, the first determination unit 220 determines a rough route to the destination based on the destination and map information, and sets an environmental landmark-based benefit function along the route. On the other hand, the first determination unit 220 does not set an environmental landmark-based benefit function for areas other than the route.

[0116] 14 , the first determination unit 220 does not set an environmental landmark-based benefit function for the space S between environmental landmarks R4 and R5. If an environmental landmark-based benefit function were set for the space S, the mobile object 100 would be recommended to travel through the location where the benefit function is set, which could result in the mobile object 100 traveling straight ahead instead of heading toward the destination. In this way, the first determination unit 220 determines a rough route to the destination based on the destination information and map information, and sets an environmental landmark-based benefit function along that route, thereby more reliably guiding the mobile object 100 to the destination.

[0117] In the remote control mode, since a destination is not set, the first determination unit 220 also sets an environmental landmark-based benefit function for the space S between the environmental landmarks R4 and R5. In the remote control mode, the user U1 can use the user terminal device 300 to control the direction of travel of the moving body 100 and the starting and stopping of the moving body 100.

[0118] In the example shown in Figure 14, the mobile body 100 travels along a route A1 corresponding to the position where the environmental landmark benefit function is set, while avoiding interfering objects (e.g., pedestrian U4 and environmental landmarks R4 to R6) without any operation by user U1.

[0119] In the remote operation mode and the delivery mode, the control device 200 controls the traveling direction of the mobile object 100 in response to an operation instruction from the user U1 using a joystick or the like of the user terminal device 300. However, if the user U1 were to operate the mobile object 100 by completely manual remote operation, this would be stressful for the user U1 due to communication delays between the mobile object 100 and the user terminal device 300. Therefore, in this embodiment, the mobile object 100 basically performs automatic driving, and when an operation instruction is received from the user U1, it changes its course left or right in accordance with the operation instruction. This reduces the stress of the user U1 when operating the mobile object 100.

[0120] FIG. 15 is a diagram illustrating a situation where user U1 instructs the moving body 100 to move leftward. In the example illustrated in FIG. 15 , when the moving body 100 travels along route A1, the distance between the moving body 100 and pedestrian U4 is short. Therefore, moving the moving body 100 to the left more reliably avoids the pedestrian U4. Therefore, when user U1 instructs the moving body 100 to move leftward using the user terminal device 300, the first determination unit 220 sets the remote control benefit function in an area to the left of the moving body 100's direction of travel (the negative side of the X-axis). Since it is recommended that the moving body 100 travel near the location where the benefit function is set, the course of the moving body 100 is changed from route A1 to route A2. This allows the moving body 100 to travel to its destination while more reliably avoiding the pedestrian U4.

[0121] Next, a method for calculating the teleoperation benefit function value will be described. As described above, the coordinates of the predicted position on the predicted trajectory in the XY coordinate system are Z ｍｊ (X ｍｊ , Y ｍｊ ) and the parameter of the operation information based on the operation of the user U1 on the user terminal device 300 is expressed as xop_j (j=1, 2, . . . , n ｍ For example, the parameter xop_j may be calculated based on the amount of operation (stroke) of a joystick or the like by the user U1, the number of operations in the operation direction, the operation time in the operation direction, etc. Note that the right direction with respect to the traveling direction of the moving body 100 is set to the positive direction of the parameter xop_j, and the left direction with respect to the traveling direction of the moving body 100 is set to the negative direction of the parameter xop_j.

[0122] The first detection unit 210 calculates a parameter xop_j based on operation information based on an operation of the user U1 on a joystick or the like, and outputs the parameter xop_j to the first determination unit 220. This allows the first detection unit 210 to detect an operation of the moving object 100 by the user U1. The first determination unit 220 also calculates a parameter xop_j based on the parameter xop_j and the X coordinate X ｍｊ The benefit function value is calculated based on the above. This point will be explained below.

[0123] 16 is a diagram illustrating an example of the remote control benefit function. As illustrated in FIG. 16, the first determination unit 220 determines the remote control benefit function Pe_b_op_j (j=1, 2, ..., n) so that the function has a gradient in the second sign direction (negative direction). ｍ The remote operation benefit function Pe_b_op_j is a function whose benefit function value decreases as Δxop_j approaches 0.

[0124] Here, Δxop_j is the sum of the parameter xop_j and the X coordinate X of the predicted position on the trajectory generated by the generation unit 260. ｍｊ Therefore, the difference Δxop_j(k) at the current time k is expressed as in equation (13).

[0125] Δxop_j(k)=X ｍｊ (k)-xop_j(k)...(13)

[0126] The first determination unit 220 calculates Δxop_j(k) based on equation (13). Furthermore, the first determination unit 220 obtains a benefit function value Pe_b_op_j(k) corresponding to the calculated Δxop_j(k) from the remote control benefit function shown in FIG.

[0127] The remote control benefit function value Pe_b_op(k) can be expressed as in equation (14). That is, the benefit function values ​​Pe_b_op_j(k) (j=1, 2, ..., n) for the coordinates of all predicted positions on the predicted trajectory are expressed as ｍ ) can be summed to obtain the teleoperation benefit function value Pe_b_op(k).

[0128] Pe_b_op(k)=Σ ｊ＝１ ｎｍ (Pe_b_op_j(k)) …(14)

[0129] 17 is a diagram illustrating how the direction of travel of the moving body 100 is changed when a remote control benefit function is set. As shown in Fig. 17, for example, when a user U1 uses the user terminal device 300 to instruct the moving body 100 to move rightward, the remote control benefit function is set to the right of the moving direction of the moving body 100 (the positive direction on the X axis).

[0130] Furthermore, since it is recommended that the moving body 100 travel to the position where the remote-control benefit function value is smallest (the position where Δxop_j = 0), the moving body 100 changes its direction of travel to the right. In this way, the first determination unit 220 determines the remote-control benefit function, so that the moving body 100 can change its direction of travel in response to the operation of the user U1.

[0131] [Calculation Process of Evaluation Function, etc.] Next, the calculation process of the evaluation function, etc. will be described. The calculation unit 250 calculates the evaluation function J(k) based on the benefit function determined by the first determination unit 220 and the risk function determined by the second determination unit 240. Specifically, the calculation unit 250 calculates the evaluation function J(k) according to the following equation (15). That is, the calculation unit 250 calculates the evaluation function J(k) by adding together Pe_b_op(k), Pe_b(k), Ptp_r(k), and Pe_r(k).

[0132] J(k)=Pe_b_op(k)+Pe_b(k)+Ptp_r(k)+Pe_r(k)...(15)

[0133] The benefit functions Pe_b_op(k) and Pe_b(k) are negative values, and the smaller the benefit function value, the higher the degree of recommendation for the moving body 100 to travel. The risk functions Ptp_r(k) and Pe_r(k) are positive values, and the larger the risk function value, the higher the degree of risk of interference between the moving body 100 and the interference target. For this reason, the generation unit 260 needs to generate a target trajectory for the moving body 100 so that the evaluation value calculated based on the evaluation function J(k) is small.

[0134] The generation unit 260 generates a target trajectory by using an arc model to model the trajectory of the moving body 100 and calculating the curvature or radius of curvature of the arc so as to change the evaluation function J(k) in the second sign direction (negative direction), as shown in FIG. 5 above. As described above, the generation unit 260 calculates the rotation angle θ ｍ１ ~θ ｍ３ and the radius of curvature R ｍ１ ~R ｍ３ The generation unit 260 then calculates an evaluation value for each of the generated trajectories using the evaluation function J(k) calculated by the calculation unit 250, and generates the trajectory with the smallest evaluation value as the target trajectory.

[0135] The control unit 270 controls the mobile body 100 based on the target trajectory generated by the generation unit 260. Specifically, the control unit 270 controls the movement mechanism 140 (drive motor, steering device, etc.) so that the mobile body 100 travels along the target trajectory generated by the generation unit 260. This allows the control device 200 to control the mobile body 100 so that it travels along a target trajectory that is suitable for the set mode (remote control mode or delivery mode) and has a low risk of interference between the mobile body 100 and an interfering object (pedestrian, obstacle, etc.).

[0136] [Specific Example of Mode Change] Next, as a specific example of mode change, an example will be described in which the mobile object 100 is used as a medical visit cart that automatically travels within a hospital. The mobile object 100 is equipped with a body temperature measuring device and a blood pressure measuring device as working equipment 180. The mobile object 100 is also installed in a nurse's station 400.

[0137] 18 is a diagram showing a state in which the mobile object 100 travels to a hospital room where a patient is located. As shown in FIG. 18, a patient P1 is lying on a bed B1, and a patient P2 is lying on a bed B2. A user U1 is a nurse working at the hospital.

[0138] The user U1 sets the hospital room of the patient P1 as the destination using the user terminal device 300, and sets the operation mode of the mobile object 100 to the delivery mode, so that the mobile object 100 automatically moves to the hospital room of the patient P1.

[0139] When the mobile object 100 arrives at the hospital room of the patient P1, the patient P1's body temperature and blood pressure are measured. Since the mobile object 100 is equipped with a body temperature measuring device and a blood pressure measuring device, the patient P1 can measure their body temperature and blood pressure by themselves using the body temperature measuring device and the blood pressure measuring device. The mobile object 100 may output guidance on body temperature and blood pressure measurement by voice from a speaker. This allows the patient P1 to understand how to measure their body temperature and blood pressure. The user U1, who is a nurse, does not need to go to the hospital room of the patient P1 with the mobile object 100, but may wait at the nurse's station 400, etc.

[0140] Next, the work data acquisition unit 284 acquires work data from the work equipment 180 mounted on the mobile object 100. For example, the work data acquisition unit 284 may acquire body temperature data of the patient P1 from a body temperature measuring device and blood pressure data of the patient P1 from a blood pressure measuring device. The work data transmission unit 286 then transmits the work data to an external information processing device using the communication device 170 mounted on the mobile object 100. For example, the work data transmission unit 286 may transmit the body temperature data and blood pressure data to the external information processing device using the communication device 170. For example, the external information processing device may be a server that manages data on hospitalized patients. This makes it possible to automatically collect work data (e.g., body temperature data and blood pressure data).

[0141] Next, the data abnormality determination unit 288 determines whether or not there is an abnormality in the work data. For example, the data abnormality determination unit 288 may determine that there is an abnormality in the work data if the body temperature of the patient P1 indicated by the body temperature data is not within a predetermined range (e.g., not less than 36.0°C and less than 37.0°C). Furthermore, the data abnormality determination unit 288 may determine that there is an abnormality in the work data if the blood pressure of the patient P1 indicated by the blood pressure data is not within a predetermined range (e.g., less than 140 / 90 mmHg).

[0142] Next, when conditions are met, including that the mobile object 100 has arrived at the destination and that an abnormality exists in the work data, the mode switching unit 282 may switch from the delivery mode to the remote operation mode. At this time, the user U1, who is a nurse, may be notified by notifying the computer of the nurse station 400 that the mode has been switched to the remote operation mode.

[0143] When the operation mode of the mobile object 100 is switched to the remote operation mode, the user U1, who is a nurse, can remotely operate the mobile object 100 using the user terminal device 300 and can converse with the patient P1 using the display device, speaker, microphone, etc. provided on the HMI 110 of the mobile object 100. This allows the user U1 to operate the mobile object 100 and check the situation if there is an abnormality in the work data (for example, body temperature data or blood pressure data).

[0144] When user U1 finishes the status check operation, the mode switching unit 282 switches the operation mode of the mobile object 100 from the remote operation mode to the delivery mode based on an instruction from the user terminal device 300. At this time, if the next hospital room to be visited is set in advance, the mode switching unit 282 may set the location of the next hospital room to be visited (e.g., the hospital room of patient P2) as the destination of the delivery mode. Note that the method of setting the destination is not limited to this. For example, the mode switching unit 282 may set the current location of user U1 as the destination of the delivery mode. Specifically, the mode switching unit 282 may receive the current location of user U1 identified using a GPS function from the user terminal device 300. Furthermore, the mode switching unit 282 may set a predetermined location, such as the nurse's station 400, as the destination of the delivery mode. This allows the mobile object 100 to automatically move to the specified location.

[0145] If there is no abnormality in the work data, the mode switching unit 282 sets the destination without switching from the delivery mode to the remote control mode, so that the mobile object 100 can automatically move to a predetermined location even if there is no abnormality in the work data.

[0146] Furthermore, when the call detection unit 290 detects a call to the mobile object 100 while the mobile object 100 is operating in the delivery mode, the mode switching unit 282 may determine whether to switch to the remote operation mode based on the content of the call. For example, when the content of the call detected by the call detection unit 290 is related to medical treatment (e.g., a request for help from a nurse), the mode switching unit 282 may switch the operation mode of the mobile object 100 to the remote operation mode. This allows the user U1 to check the status of the person who called out to the mobile object 100 by operating the mobile object 100.

[0147] On the other hand, if it is determined not to switch to the remote operation mode, the response output unit 292 may generate a response to the call detected by the call detection unit 290 and output the response. For example, the response output unit 292 may automatically generate a response to a greeting or a simple conversation and output it from a speaker provided in the HMI 110. This can save the user U1 the trouble of responding to someone who calls out to the mobile object 100.

[0148] Furthermore, when setting the delivery mode, the user terminal device 300 may select a mobile body 100 to be used in the delivery mode from among a plurality of waiting mobile bodies 100. For example, the user terminal device 300 may select one of the plurality of mobile bodies 100 based on at least one of the type of work equipment 180 mounted on each of the plurality of mobile bodies 100, the location of each of the plurality of mobile bodies 100, and the state of charge of each of the plurality of mobile bodies 100. This allows the user terminal device 300 to select the optimal mobile body 100 to be used in the delivery mode.

[0149] The computer of the nurse station 400 may have the same configuration and functions as the user terminal device 300, so that the mobile object 100 can be remotely controlled from the computer of the nurse station 400. This allows the user U1 to remotely control the mobile object 100 while waiting at the nurse station 400.

[0150] 19 is a flowchart showing an example of processing executed by the control device 200. The processing according to this flowchart is executed in response to the activation of the moving body 100.

[0151] First, the mode switching unit 282 sets the delivery mode based on an instruction from the user U1 (step S101). At this time, the mode switching unit 282 also sets a destination based on the instruction from the user U1. For example, the mode switching unit 282 may accept instructions from the user U1 based on information input by the user U1 to the user terminal device 300. Alternatively, the mode switching unit 282 may accept instructions from the user U1 in response to the user U1's operation on the HMI 110. Alternatively, the mode switching unit 282 may accept instructions from the user U1 by detecting a gesture by the user U1 using the camera 80. Furthermore, the mode switching unit 282 may recognize a voice uttered by the user using a voice recognition function and accept instructions from the user U1 based on the recognized voice. By setting the delivery mode, the vehicle 100 travels toward the destination.

[0152] Next, the determination unit 280 determines whether the mobile object 100 has arrived at the destination (step S102). For example, the determination unit 280 may determine that the mobile object 100 has arrived at the destination when the current location of the mobile object 100 identified by the position identification device 130 is within a predetermined distance from the location of the destination. If the mobile object 100 has not arrived at the destination, the determination unit 280 waits until the mobile object 100 arrives at the destination.

[0153] On the other hand, when the mobile object 100 arrives at the destination, the work data acquisition unit 284 acquires work data from the work equipment 180 mounted on the mobile object 100 (step S103). For example, if the work equipment 180 is a body temperature measuring device or a blood pressure measuring device, the work data acquisition unit 284 acquires body temperature data or blood pressure data as work data from the work equipment 180. At this time, the work data transmission unit 286 uses the communication device 170 to transmit the work data to an external information processing device (such as a server that manages patient data).

[0154] Next, the data abnormality determination unit 288 determines whether or not there is an abnormality in the work data (step S104). For example, the data abnormality determination unit 288 may determine that there is an abnormality in the work data if the value indicated by the work data is not within a preset range.

[0155] If it is determined that there is an abnormality in the work data, the mode switching unit 282 switches the operation mode of the mobile object 100 to the remote operation mode (step S105), which allows the user U1 to remotely operate the mobile object 100 using the user terminal device 300.

[0156] On the other hand, if it is determined that there is no abnormality in the work data, the mode switching unit 282 does not switch from the delivery mode to the remote control mode. At this time, the mode switching unit 282 sets the destination in the delivery mode as the next destination. This allows the mobile object 100 to automatically move to a predetermined location even if there is no abnormality in the work data.

[0157] According to the control device 200 of this embodiment, the target trajectory of the moving body 100 is generated by modeling the trajectory of the moving body 100 using an arc model, thereby making it possible to smooth the movement of the moving body 100. This makes it easier for traffic participants (pedestrians, etc.) to predict the behavior of the moving body 100, and makes it possible to effectively prevent contact between the moving body 100 and other traffic participants.

[0158] As described above, the control device 200 of this embodiment is a device that operates the mobile object 100 by switching between a delivery mode in which the mobile object 100 travels to a destination and a remote control mode in which the user U1 remotely operates the mobile object 100, and includes a determination unit 280, a mode switching unit 282, a generation unit 260, and a control unit 270. The determination unit 280 determines whether the mobile object 100 has arrived at the destination. The mode switching unit 282 switches the operation mode of the mobile object 100 from the delivery mode to the remote control mode when conditions are met, including that the mobile object 100 has arrived at the destination, while the mobile object 100 is operating in the delivery mode. The generation unit 260 generates a target trajectory for the mobile object 100 based on the switched operation mode. The control unit 270 controls the mobile object 100 based on the target trajectory. In this way, the control device 200 of this embodiment can cause the mobile object 100 to travel by switching between the delivery mode and the remote control mode.

[0159] The above-described embodiment can be expressed as follows: A control device comprising: a storage device storing a program; and a hardware processor that operates a mobile object by switching between a delivery mode in which the mobile object travels to a destination and a remote operation mode in which the user remotely operates the mobile object, wherein the hardware processor executes the program stored in the storage device to perform the following processes: determining whether the mobile object has arrived at the destination; switching the operation mode of the mobile object from the delivery mode to the remote operation mode when a condition including that the mobile object has arrived at the destination is met while the mobile object is operating in the delivery mode; generating a target trajectory of the mobile object based on the switched operation mode; and controlling the mobile object based on the target trajectory.

[0160] The above describes the form for carrying out the present invention using an embodiment, but the present invention is not limited to such an embodiment, and various modifications and substitutions can be made within the scope that does not deviate from the gist of the present invention.

[0161] REFERENCE SIGNS LIST 100 Mobile object 200 Control device 210 First detection unit 220 First determination unit 230 Second detection unit 240 Second determination unit 250 Calculation unit 260 Generation unit 270 Control unit 280 Determination unit 282 Mode switching unit 284 Work data acquisition unit 286 Work data transmission unit 288 Data abnormality determination unit 290 Call detection unit 292 Response output unit 300 User terminal device

Claims

1. A control device that operates a mobile body by switching between a delivery mode in which the mobile body travels to a destination and a remote control mode in which the user remotely controls the mobile body, comprising: a determination unit that determines whether the mobile body has arrived at the destination; a mode switching unit that switches the operation mode of the mobile body from the delivery mode to the remote control mode when a condition is met that includes the mobile body having arrived at the destination while the mobile body is operating in the delivery mode; a generation unit that generates a target trajectory for the mobile body based on the switched operation mode; and a control unit that controls the mobile body based on the target trajectory.

2. The control device according to claim 1, further comprising: a work data acquisition unit that acquires work data from work equipment mounted on the mobile body; and a work data transmission unit that transmits the work data to an external information processing device using a communication device mounted on the mobile body.

3. The control device according to claim 2, further comprising a data abnormality determination unit that determines whether there is an abnormality in the work data, and the mode switching unit switches from the delivery mode to the remote operation mode when conditions are met, including that the mobile body has arrived at the destination and that there is an abnormality in the work data.

4. A control device as described in claim 1, further comprising a call detection unit that detects a call to the mobile body, and wherein when a call to the mobile body is detected while the mobile body is operating in the delivery mode, the mode switching unit determines whether to switch to the remote control mode based on the content of the call.

5. The control device according to claim 4, further comprising: a response output unit that generates a response to the call and outputs the response when it is determined not to switch to the remote control mode.

6. A mobile body system comprising a plurality of mobile bodies and a terminal device capable of communicating with said plurality of mobile bodies, wherein each of said plurality of mobile bodies is equipped with a control device as set forth in any one of claims 1 to 5, and said terminal device selects one of said plurality of mobile bodies based on at least one of the type of work equipment mounted on each of said plurality of mobile bodies, the position of each of said plurality of mobile bodies, and the state of charge of each of said plurality of mobile bodies.

7. A control method in which a control device that operates a mobile body by switching between a delivery mode in which the mobile body travels to a destination and a remote control mode in which the user remotely controls the mobile body executes the following control methods: a process of determining whether the mobile body has arrived at the destination; a process of switching the operation mode of the mobile body from the delivery mode to the remote control mode when a condition including that the mobile body has arrived at the destination is met while the mobile body is operating in the delivery mode; a process of generating a target trajectory for the mobile body based on the switched operation mode; and a process of controlling the mobile body based on the target trajectory.

8. A program for causing a processor of a control device that operates a mobile body by switching between a delivery mode in which the mobile body travels to a destination and a remote control mode in which the user remotely controls the mobile body, to execute the following processes: a process for determining whether the mobile body has arrived at the destination; a process for switching the operation mode of the mobile body from the delivery mode to the remote control mode when a condition including that the mobile body has arrived at the destination is met while the mobile body is operating in the delivery mode; a process for generating a target trajectory for the mobile body based on the switched operation mode; and a process for controlling the mobile body based on the target trajectory.

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