Control device, control method, and system

Abstract

To provide a technique for reducing a possibility that cycle delay occurs in control of a mobile object.SOLUTION: A control device generates a control command for controlling a mobile object using three-dimensional point group data on the mobile object measured by a distance measurement device. The control device comprises: a range identification section that identifies a use range that is a range including only some pieces of the three-dimensional point group data; and an estimation section that estimates at least one of a position and an orientation of the mobile object using the three-dimensional point group data in the use range.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present disclosure relates to a control device, a control method, and a system for a moving body.

Background Art

[0002] In the vehicle manufacturing process, a technology for self-propelling a vehicle is known (for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When moving a moving body such as a vehicle by self-propelled conveyance, a process of estimating the position and orientation of the moving body is executed. The position and orientation of the moving body can be estimated using three-dimensional point cloud data acquired using a distance measuring device such as a camera or a radar. This estimation process needs to be calculated at a high frequency for stabilizing the running control of the moving body. However, since a long processing time is required to process a large amount of three-dimensional point cloud data, there is a possibility that a cycle delay occurs in the control of the moving body.

Means for Solving the Problems

[0005] The present disclosure can be realized in the following forms.

[0006] (1) According to the first aspect of the present disclosure, LiDARA control device is provided that generates a control command for controlling the moving body using the three-dimensional point cloud data of the moving body measured using []. This control device includes a range specifying unit that specifies a usage range that is a range including only a part of the three-dimensional point cloud data, and an estimating unit that estimates at least one of the position and orientation of the moving body using the three-dimensional point cloud data of the usage range. The usage range is specified to include a characteristic part determined according to the type of the moving body. Alternatively, the usage range is specified to include a characteristic part in the observation area of the moving body that can be observed in [] where the density of the point cloud is higher than the average value in the observation area. LiDAR It is specified to include a characteristic part in the observation area of the moving body that can be observed in [] where the density of the point cloud is higher than the average value in the observation area. According to this control device, since at least one of the position and orientation of the moving body is estimated using only a part of the three-dimensional point cloud data, the possibility of a cycle delay occurring in the control of the moving body can be reduced. (2) In the above control device, the range specifying unit may execute the process of specifying the usage range when the processing load of the control device is greater than a preset reference value, and may not execute the process of specifying the usage range when the processing load is less than or equal to the reference value. According to this control device, when the processing load of the control device is high, the possibility of a cycle delay occurring in the control of the moving body can be reduced. (3) According to the second aspect of the present disclosure, a control method for a moving body is provided. This control method includes (a) LiDAR a step of acquiring the three-dimensional point cloud data of the moving body measured using [], (b) a step of specifying a usage range that is a range including only a part of the three-dimensional point cloud data, (c) a step of estimating at least one of the position and orientation of the moving body using the three-dimensional point cloud data of the usage range, and (d) a step of generating a control command for controlling the moving body using at least one of the position and orientation of the moving body. The usage range is specified to include a characteristic part determined according to the type of the moving body. Alternatively, the usage range is specified to include a characteristic part in the observation area of the moving body that can be observed in [] where the density of the point cloud is higher than the average value in the observation area. LiDAR It is specified to include a characteristic part in the observation area of the moving body that can be observed in [] where the density of the point cloud is higher than the average value in the observation area. According to this control method, since at least one of the position and orientation of the moving object is estimated using only a part of the three-dimensional point cloud data, it is possible to reduce the possibility of a periodic delay occurring in the control of the moving object. (4) According to a third aspect of the present disclosure, a system for controlling a moving object is provided. This system measures the three-dimensional point cloud data of the moving object LiDAR and a control device that generates a control command for controlling the moving object using the three-dimensional point cloud data. The control device includes a range specifying unit that specifies a use range that is a range including only a part of the three-dimensional point cloud data, and an estimation unit that estimates at least one of the position and orientation of the moving object using the three-dimensional point cloud data in the use range. The use range is specified so as to include a characteristic part determined according to the type of the moving object. Alternatively, the use range is specified so as to include a characteristic part in which the density of the point cloud is higher than the average value in the observation region of the moving object that can be observed in the LiDAR observation region. According to this system, since at least one of the position and orientation of the moving object is estimated using only a part of the three-dimensional point cloud data, it is possible to reduce the possibility of a periodic delay occurring in the control of the moving object.

Brief Description of the Drawings

[0007]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Modes for Carrying Out the Invention

[0008] A. First Embodiment FIG. 1 is a conceptual diagram showing the configuration of a remote control system 10 in an embodiment. The remote control system 10 includes one or more vehicles 100 as mobile bodies, a remote control device 200 that generates a control command for remotely controlling the vehicle 100 and transmits it to the vehicle 100, a plurality of distance measuring devices 300 that measure three-dimensional point cloud data of the vehicle 100, and a process management device 400 that manages the manufacturing process of the vehicle 100. In the first embodiment, the remote control device 200 corresponds to the "control device" of the present disclosure.

[0009] The vehicle 100 is preferably a battery electric vehicle (BEV). Note that the mobile body is not limited to an electric vehicle, and may be, for example, a gasoline vehicle, a hybrid vehicle, or a fuel cell vehicle. The mobile body is not limited to the vehicle 100, and may be, for example, an electric vertical takeoff and landing aircraft (so-called flying car).

[0010] In the present disclosure, the "mobile body" means an object that can move. The vehicle may be a vehicle that travels on wheels or a vehicle that travels on an endless track, and may be, for example, a passenger car, a truck, a bus, a two-wheeled vehicle, a four-wheeled vehicle, a tank, a construction vehicle, etc. When the mobile body is other than a vehicle, the expressions "vehicle" and "car" in the present disclosure can be appropriately replaced with "mobile body", and the expression "travel" can be appropriately replaced with "move".

[0011] Vehicle 100 is configured to be capable of traveling by autonomous driving. "Autonomous driving" means driving without relying on the driving operations of passengers. The driving operations refer to operations related to at least any one of "driving forward", "turning", and "stopping" of vehicle 100. Autonomous driving is realized by automatic or manual remote control using a device located outside vehicle 100, or by autonomous control of vehicle 100. In vehicle 100 traveling by autonomous driving, a passenger who does not perform driving operations may board. Passengers who do not perform driving operations include, for example, a person simply sitting on the seat of vehicle 100, or a person performing operations different from driving operations, such as assembly, inspection, and operation of switches, while boarding vehicle 100. Note that driving by the driving operations of passengers may be called "driver-operated driving".

[0012] In this specification, "remote control" includes "full remote control" in which all the operations of vehicle 100 are completely determined from outside vehicle 100, and "partial remote control" in which a part of the operations of vehicle 100 is determined from outside vehicle 100. Also, "autonomous control" includes "full autonomous control" in which vehicle 100 autonomously controls its own operations without receiving any information from a device outside vehicle 100, and "partial autonomous control" in which vehicle 100 autonomously controls its own operations using information received from a device outside vehicle 100.

[0013] In this embodiment, in the factory where vehicle 100 is manufactured, remote control of vehicle 100 is executed. The factory includes a first location PL1 and a second location PL2. The first location PL1 is, for example, a location where vehicle 100 is assembled, and the second location PL2 is, for example, a location where vehicle 100 is inspected. The first location PL1 and the second location PL2 are connected by a travel route SR on which vehicle 100 can travel. Any position within the factory is represented by the xyz coordinate values of a reference coordinate system Σr.

[0014] A plurality of ranging devices 300 for measuring the vehicle 100 are installed around the travel path SR. The remote control device 200 can acquire the relative position and orientation of the vehicle 100 with respect to the target route TR in real time using the three-dimensional point cloud data measured by each ranging device 300. As the ranging device 300, a camera or LiDAR (Light Detection And Ranging) can be used. In particular, LiDAR is preferable in that high-precision three-dimensional point cloud data can be obtained. The positions of the individual ranging devices 300 are fixed, and the relative relationship between the reference coordinate system Σr and the device coordinate system of each ranging device 300 is known. A coordinate transformation matrix for mutually converting the coordinate values of the reference coordinate system Σr and the coordinate values of the device coordinate system of each ranging device 300 is stored in advance in the remote control device 200.

[0015] The remote control device 200 generates a control command for causing the vehicle 100 to travel along the target route TR and transmits the control command to the vehicle 100. The vehicle 100 travels according to the received control command. Therefore, by the remote control system 10, the vehicle 100 can be remotely controlled to move from the first place PL1 to the second place PL2 without using a conveying device such as a crane or a conveyor.

[0016] FIG. 2 is a block diagram showing the configurations of the vehicle 100 and the remote control device 200. The vehicle 100 includes a vehicle control device 110 for controlling each part of the vehicle 100, an actuator group 120 driven under the control of the vehicle control device 110, a communication device 130 for communicating with the remote control device 200 via wireless communication, and a GPS receiver 140 for acquiring the position information of the vehicle 100. In the present embodiment, the actuator group 120 includes an actuator of a driving device for accelerating the vehicle 100, an actuator of a steering device for changing the traveling direction of the vehicle 100, and an actuator of a braking device for decelerating the vehicle 100. The driving device includes a battery, a traveling motor driven by the power of the battery, and driving wheels rotated by the traveling motor. The actuator of the driving device includes the traveling motor. Note that the actuator group 120 may further include an actuator for swinging the wiper of the vehicle 100, an actuator for opening and closing the power window of the vehicle 100, and the like.

[0017] The vehicle control device 110 is configured by a computer including a processor 111, a memory 112, an input / output interface 113, and an internal bus 114. The processor 111, the memory 112, and the input / output interface 113 are connected to be communicable bidirectionally via the internal bus 114. The actuator group 120, the communication device 130, and the GPS receiver 140 are connected to the input / output interface 113.

[0018] In this embodiment, the processor 111 functions as a vehicle control unit 115 and a position information acquisition unit 116 by executing a program PG1 prestored in the memory 112. The vehicle control unit 115 controls the actuator group 120. When a driver is on board the vehicle 100, the vehicle control unit 115 can control the actuator group 120 according to the driver's operation to drive the vehicle 100. Regardless of whether a driver is on board the vehicle 100 or not, the vehicle control unit 115 can also control the actuator group 120 according to a control command transmitted from the remote control device 200 to drive the vehicle 100. The position information acquisition unit 116 acquires position information indicating the current location of the vehicle 100 by using the GPS receiver 140. However, the position information acquisition unit 116 and the GPS receiver 140 can be omitted.

[0019] The remote control device 200 is constituted by a computer including a processor 201, a memory 202, an input / output interface 203, and an internal bus 204. The processor 201, the memory 202, and the input / output interface 203 are connected via the internal bus 204 so as to be communicable bidirectionally. A communication device 205 for communicating with the vehicle 100, the distance measuring device 300, and the process management device 400 by wireless communication is connected to the input / output interface 203.

[0020] In this embodiment, the processor 201 functions as a three-dimensional point cloud data acquisition unit 210, a range specification unit 220, an estimation unit 230, and a remote control command generation unit 240 by executing a program PG2 prestored in the memory 202.

[0021] The three-dimensional point cloud data acquisition unit 210 acquires the three-dimensional point cloud data measured by the distance measuring device 300. The three-dimensional point cloud data is data indicating the three-dimensional positions of the point cloud detected by the distance measuring device 300.

[0022] The range specification unit 220 specifies a usage range which is a range including only a part of the three-dimensional point cloud data. The specific method will be described later.

[0023] The estimation unit 230 estimates the position and orientation of the vehicle 100 using the three-dimensional point cloud data of the usage range specified by the range specification unit 220. In the present embodiment, the estimation unit 230 estimates the position and orientation of the vehicle 100 by performing template matching using the template point cloud TP stored in the memory 202. Note that when the three-dimensional point cloud data is not available, the estimation unit 230 can estimate the position and orientation of the vehicle 100 using the driving history of the vehicle 100 and the position information detected by the GPS receiver 140 mounted on the vehicle 100. The estimation unit 230 may estimate only one of the position and orientation of the vehicle 100. In this case, the other of the position and orientation of the vehicle 100 is determined using the driving history of the vehicle 100 or the like.

[0024] The position and orientation of the vehicle are also referred to as "vehicle position information". In the present embodiment, the vehicle position information includes the position and orientation of the vehicle 100 in the reference coordinate system of the factory.

[0025] The remote control command generation unit 240 generates a control command for remote control using the estimated position and orientation of the vehicle 100 and transmits it to the vehicle 100. This control command is a command to make the vehicle 100 travel according to the target route TR stored in the memory 202. The control command can be generated as a command including a driving force or a braking force and a steering angle. Alternatively, the control command may be generated as a command including at least one of the position and orientation of the vehicle 100 and the future driving route.

[0026] In the present embodiment, the control command includes the acceleration and steering angle of the vehicle 100 as parameters. In other embodiments, the control command may include the speed of the vehicle 100 as a parameter instead of or in addition to the acceleration of the vehicle 100.

[0027] The project management device 400 executes the overall management of the manufacturing process of the vehicle 100 in the factory. For example, when one vehicle 100 starts traveling along the target route TR, the individual information indicating the identification number, model, etc. of the vehicle 100 is transmitted from the project management device 400 to the remote control device 200. The position of the vehicle 100 detected by the remote control device 200 is also transmitted to the project management device 400. Note that the functions of the project management device 400 may be implemented in the same device as the remote control device 200.

[0028] The remote control device 200 is also referred to as a "server", and the distance measuring device 300 is also referred to as an "external sensor". Also, the control command is also referred to as a "travel control signal", the target route TR is also referred to as a "reference route", and the reference coordinate system is also referred to as a "global coordinate system".

[0029] FIG. 3 is a flowchart showing the processing procedure of remote control in the first embodiment. The processing of the remote control device 200 is executed at regular intervals. Alternatively, the processing of the remote control device 200 shown in FIG. 3 may be executed each time the three-dimensional point cloud data acquisition unit 210 newly acquires three-dimensional point cloud data from the distance measuring device 300 responsible for measuring the vehicle 100 to be controlled. The three-dimensional point cloud data acquisition unit 210 may perform preprocessing to remove the background point cloud data representing stationary objects from the newly acquired three-dimensional point cloud data.

[0030] In step S10, the range specifying unit 220 determines whether the processing load of the remote control device 200 is greater than the reference value. The processing load of the remote control device 200 is, for example, the usage rate of the processor 201. The reference value of the processing load is determined considering the speed of the vehicle 100, and is set as a value that can achieve the desired processing speed for stable travel control. Alternatively, the reference value of the processing load may be a predetermined constant value.

[0031] When the processing load is less than or equal to the reference value, the process proceeds to step S50, and the estimation unit 230 estimates the position and orientation of the vehicle 100 by performing matching between all the three-dimensional point cloud data and the template point cloud TP. Note that the phrase "all the three-dimensional point cloud data" means the three-dimensional point cloud data without specifying the range of use. As described above, preprocessing for removing the background point cloud data may be performed on this three-dimensional point cloud data.

[0032] On the other hand, when the processing load is greater than the reference value, the process proceeds to step S20, and the range specifying unit 220 specifies a range of use that includes only a part of the three-dimensional point cloud data.

[0033] FIG. 4 is an explanatory diagram showing a process of specifying the range of use of the three-dimensional point cloud data. As shown in the upper part of FIG. 4, when the processing load is less than or equal to the reference value, the entire range Ra of the three-dimensional point cloud data measured by the distance measuring device 300 is used as it is. On the other hand, as shown in the lower part of FIG. 4, when the processing load is greater than the reference value, only the three-dimensional point cloud data within a range of use Ru that is smaller than the entire range Ra of the three-dimensional point cloud data measured by the distance measuring device 300 is used. The range of use Ru means a range narrower than the entire range Ra of the viewing field of the distance measuring device 300. The number of point clouds detected in this range of use Ru is smaller than the number of point clouds detected in the entire range Ra. The reason for making the range of use Ru narrower than the entire range Ra is that if only a part of the three-dimensional point cloud data is used, the estimation speed of the position and orientation of the vehicle 100 can be increased, and the possibility of a cycle delay in remote control can be reduced.

[0034] The usage range Ru is preferably specified to include a feature portion CP in the observation region of the vehicle 100 that can be observed by the distance measuring device 300, where the density of the feature amount is higher than the average value in the observation region. In the example of FIG. 4, a prominent portion of the rear of the vehicle 100 is shown as the feature portion CP. The feature amount is, for example, the amount of edge, and is the amount of feature points extracted by applying a feature point extraction operator to the image of the vehicle 100. The observation region of the vehicle 100 is, for example, the region of the entire rear of the vehicle 100. By specifying the usage range Ru to include the feature portion CP with a large feature amount in this way, a point group suitable for estimating the position and orientation of the vehicle 100 can be used.

[0035] The range of the feature portion CP for specifying the usage range Ru can be determined, for example, by any of the following methods. <Determination method M1 of the feature portion CP> Determine the feature portion CP according to the type of the vehicle 100, the detection direction of the vehicle 100 by the distance measuring device 300, and the distance between the distance measuring device 300 and the vehicle 100. The model of the vehicle 100 can be determined from the individual information transmitted from the process management device 400 to the remote control device 200. Alternatively, the remote control device 200 may acquire the model of the vehicle 100 by wireless communication with the vehicle 100. Note that the model of the vehicle 100 may be information representing the external shape of the vehicle 100 or may be an in-house serial number. The detection direction of the vehicle 100 by the distance measurement device 300 can be determined from the position of the portion where the point cloud is dense in the three-dimensional point cloud data. For example, a bounding box surrounding the portion where the point cloud is dense may be determined, and the direction from the distance measurement device 300 toward the reference position of the bounding box may be determined as the "detection direction". The distance between the distance measurement device 300 and the vehicle 100 can be determined, for example, as the distance from the distance measurement device 300 to the reference position of the bounding box. The shape and position of the characteristic portion CP are determined according to the model of the vehicle, and the positional relationship between the bounding box of the point cloud and the characteristic portion CP is also determined according to the model of the vehicle. Therefore, these pieces of information are stored as vehicle information VI for each model. Accordingly, if the model of the vehicle 100, the detection direction of the vehicle 100 by the distance measurement device 300, and the distance between the distance measurement device 300 and the vehicle 100 are known, the position and shape of the characteristic portion CP can be determined accordingly.

[0036] <Determination method M2 of the characteristic portion CP> Determine the characteristic portion CP according to the density of the point cloud in the three-dimensional point cloud data. Among the three-dimensional point cloud data, since the portion with a high point cloud density also has many feature quantities, the portion with a high point cloud density can be determined as the characteristic portion CP. For example, a bounding box surrounding the portion where the point cloud is dense is determined, the bounding box is divided into a plurality of voxels (micro boxes), the density of the point cloud is calculated for each voxel, and the portion where the voxels with a point cloud density equal to or higher than the density reference value are aggregated can be determined as the characteristic portion CP.

[0037] The usage range Ru is set as a range including the feature portion CP. In the example of FIG. 4, the usage range Ru is set as a range wider than the range circumscribing the feature portion CP. In this way, even when the accuracy of the determination process of the position and shape of the feature portion CP is low, the usage range Ru can be set so as to surely include the feature portion CP.

[0038] In step S30, the estimation unit 230 extracts the three-dimensional point cloud data of the usage range Ru. In step S40, the estimation unit 230 estimates the position and orientation of the vehicle 100 by performing matching between the three-dimensional point cloud data of the usage range Ru and the template point cloud TP.

[0039] In step S60, using the position and orientation of the vehicle 100 estimated in step S40 or step S50, the remote control command generation unit 240 generates a control command value and transmits it to the vehicle 100. The details of step S60 are as follows.

[0040] In step S60, the remote control command generation unit 240 first determines a target position to which the vehicle 100 should head, using vehicle position information including the position and orientation of the vehicle 100 and the target route TR. The remote control command generation unit 240 determines the target position on the target route TR ahead of the current position of the vehicle 100, and generates a control command value for driving the vehicle 100 toward the target position. In the present embodiment, the control command value includes the acceleration and steering angle of the vehicle 100 as parameters. The remote control command generation unit 240 calculates the traveling speed of the vehicle 100 from the change in the position of the vehicle 100, and compares the calculated traveling speed with the target speed. Overall, when the traveling speed is lower than the target speed, the remote control command generation unit 240 determines the acceleration so that the vehicle 100 accelerates, and when the traveling speed is higher than the target speed, the remote control command generation unit 240 determines the acceleration so that the vehicle 100 decelerates. Further, when the vehicle 100 is located on the target route TR, the remote control command generation unit 240 determines the steering angle and acceleration so that the vehicle 100 does not deviate from the target route TR, and when the vehicle 100 is not located on the target route TR, in other words, when the vehicle 100 has deviated from the target route TR, the remote control command generation unit 240 determines the steering angle and acceleration so that the vehicle 100 returns to the target route TR. In other embodiments, the control command value may include the speed of the vehicle 100 as a parameter instead of or in addition to the acceleration of the vehicle 100. The control command value thus generated is transmitted from the remote control device 200 to the vehicle 100.

[0041] The control process by the processor 111 of the vehicle 100 includes step S70 and step S80. In step S70, the vehicle control unit 115 waits until it acquires the control command value from the remote control device 200. When the control command value is acquired, the process proceeds to step S80, and the vehicle control unit 115 controls the actuator group 120 according to the acquired control command value. According to the remote control system 10 of the present embodiment, the vehicle 100 can be driven by remote control, and the vehicle 100 can be moved along the target route TR without using a conveying facility such as a crane or a conveyor.

[0042] In the processing procedure of FIG. 3 described above, the use range Ru of the three-dimensional point cloud data was restricted only when the processing load of the remote control device 200 was large, but the use range Ru may always be restricted regardless of the processing load. In this case, steps S10 and S60 are omitted.

[0043] As described above, in the first embodiment, the use range Ru, which is a range including only a part of the three-dimensional point cloud data, is specified, and at least one of the position and orientation of the moving body is estimated using the three-dimensional point cloud data in the use range Ru. Therefore, the possibility of a cycle delay in remote control can be reduced.

[0044] In the above embodiment, the vehicle 100 only needs to be configured to be movable by remote control. For example, it may be in the form of a platform having the configuration described below. Specifically, the vehicle 100 only needs to include at least a vehicle control unit 115 and a communication device 150 in order to exhibit the three functions of "running", "turning", and "stopping" by remote control. That is, for the vehicle 100 that can be moved by remote control, at least a part of the interior parts such as the driver's seat and the dashboard may not be installed, at least a part of the exterior parts such as the bumper and the fender may not be installed, and the body shell may not be installed. In this case, the remaining parts such as the body shell may be installed on the vehicle 100 before the vehicle 100 is shipped from the factory, or the vehicle 100 may be shipped from the factory with the remaining parts such as the body shell not installed, and then the remaining parts such as the body shell may be installed on the vehicle 100. Note that positioning can be performed in the same manner as the vehicle 100 in each embodiment for the form of the platform.

[0045] B. Second Embodiment FIG. 5 is a block diagram showing the configurations of the vehicle 100 and the remote control device 200 in the second embodiment. The differences from the configuration of the first embodiment shown in FIG. 2 are mainly the following three points. (1) The functions of the three-dimensional point cloud data acquisition unit 121, the range identification unit 122, the estimation unit 123, and the control command generation unit 124 are added to the functions of the processor 111 of the vehicle 100. (2) The template point cloud TP, the vehicle information VI, and the target route TR are stored in the memory 112 of the vehicle 100. (3) The functions of the three-dimensional point cloud data acquisition unit 210, the range identification unit 220, the estimation unit 230, and the remote control command generation unit 240 are omitted from the functions of the processor 201 of the remote control device 200.

[0046] The functions of the three-dimensional point cloud data acquisition unit 121, the range identification unit 122, the estimation unit 123, and the control command generation unit 124 are substantially the same as the functions of the three-dimensional point cloud data acquisition unit 210, the range identification unit 220, the estimation unit 230, and the remote control command generation unit 240, respectively, and thus their descriptions are omitted.

[0047] In the second embodiment, the vehicle 100 executes a process of specifying a usage range Ru, which is a range including only a part of the three-dimensional point cloud data, and estimating at least one of the position and orientation of the vehicle 100 using the three-dimensional point cloud data of the usage range Ru. That is, in the second embodiment, the vehicle control device 110 of the vehicle 100 corresponds to the "control device" of the present disclosure.

[0048] FIG. 6 is a flowchart showing the processing procedure of vehicle control in the second embodiment. Steps S110 to S160 in FIG. 6 respectively correspond to steps S10 to S60 in the first embodiment shown in FIG. 3. However, in step S160, since the control command value is created by the control command generation unit 124 of the vehicle 100, the control of the actuator group 120 of the vehicle 100 is executed without transmitting and receiving the control command value between the remote control device 200 and the vehicle 100.

[0049] Note that the template point cloud TP, vehicle information VI, and target route TR are stored in the memory 112 of the vehicle 100 before the vehicle 100 starts traveling along the target route TR. These data may be supplied from the remote control device 200 or the process management device 400, or may be written into the memory 112 of the vehicle 100 using other means.

[0050] As described above, also in the second embodiment, similar to the first embodiment, a usage range Ru that is a range including only a part of the three-dimensional point cloud data is specified, and at least one of the position and orientation of the moving body is estimated using the three-dimensional point cloud data of the usage range Ru. Therefore, the possibility of a cycle delay occurring in the control of the vehicle can be reduced.

[0051] C. Other Embodiments In each of the various embodiments described below, "server 200" means the remote control device 200, and "external sensor" means the distance measuring device 300. Also, "travel control signal" means a control command, "reference route" means the target route TR, and "global coordinate system" means the reference coordinate system Σr.

[0052] (C1) In each of the above embodiments, the external sensor is a LiDAR (Light Detection And Ranging). In contrast, the external sensor does not have to be a LiDAR, and for example, it may be a camera. When the external sensor is a camera, the server 200 detects the outer shape of the vehicle 100 from the captured image, for example, calculates the coordinates of the measurement points of the vehicle 100 in the coordinate system of the captured image, that is, the local coordinate system, and converts the calculated coordinates into coordinates in the global coordinate system, thereby obtaining the position of the vehicle 100. The outer shape of the vehicle 100 included in the captured image can be detected, for example, by inputting the captured image into a detection model that utilizes artificial intelligence. The detection model is prepared, for example, inside or outside the system 10 and is pre-stored in the memory of the server 200. Examples of the detection model include a learned machine learning model trained to realize either semantic segmentation or instance segmentation. As this machine learning model, for example, a convolutional neural network (hereinafter, CNN) trained by supervised learning using a learning dataset can be used. The learning dataset has, for example, a plurality of training images including the vehicle 100 and a label indicating whether each region in the training image is a region indicating the vehicle 100 or a region indicating other than the vehicle 100. During the learning of the CNN, it is preferable that the parameters of the CNN are updated so as to reduce the error between the output result by the detection model and the label by backpropagation (error backpropagation method). Further, the server 200 can obtain the orientation of the vehicle 100, for example, by estimating based on the direction of the movement vector of the vehicle 100 calculated from the position change of the feature points of the vehicle 100 between frames of the captured image using the optical flow method.

[0053] (C2) In the first embodiment, the server 200 executes the processes from the acquisition of the vehicle position information including the position and orientation of the vehicle 100 to the generation of the driving control signal. In contrast, at least a part of the processes from the acquisition of the vehicle position information to the generation of the driving control signal may be executed by the vehicle 100. For example, the following forms (1) to (3) may be used.

[0054] (1) The server 200 may acquire vehicle position information, determine a target position to which the vehicle 100 should next head, and generate a route from the current position of the vehicle 100 represented in the acquired vehicle position information to the target position. The server 200 may generate a route to the target position between the current position and the destination, or may generate a route to the destination. The server 200 may transmit the generated route to the vehicle 100. The vehicle 100 may generate a travel control signal so that the vehicle 100 travels on the route received from the server 200, and control an actuator of the vehicle 100 using the generated travel control signal.

[0055] (2) The server 200 may acquire vehicle position information and transmit the acquired vehicle position information to the vehicle 100. The vehicle 100 may determine a target position to which the vehicle 100 should next head, generate a route from the current position of the vehicle 100 represented in the received vehicle position information to the target position, generate a travel control signal so that the vehicle 100 travels on the generated route, and control an actuator of the vehicle 100 using the generated travel control signal.

[0056] (3) In the forms (1) and (2) above, an internal sensor is mounted on the vehicle 100, and the detection result output from the internal sensor may be used for at least one of the generation of the route and the generation of the driving control signal. The internal sensor is a sensor mounted on the vehicle 100. Specifically, the internal sensor may include, for example, a camera, LiDAR, millimeter-wave radar, ultrasonic sensor, GPS sensor, acceleration sensor, gyro sensor, etc. For example, in the form (1) above, the server 200 may acquire the detection result of the internal sensor and reflect the detection result of the internal sensor in the route when generating the route. In the form (1) above, the vehicle 100 may acquire the detection result of the internal sensor and reflect the detection result of the internal sensor in the driving control signal when generating the driving control signal. In the form (2) above, the vehicle 100 may acquire the detection result of the internal sensor and reflect the detection result of the internal sensor in the route when generating the route. In the form (2) above, the vehicle 100 may acquire the detection result of the internal sensor and reflect the detection result of the internal sensor in the driving control signal when generating the driving control signal.

[0057] (C3) In each of the above embodiments, an internal sensor is mounted on the vehicle 100, and the detection result output from the internal sensor may be used for at least one of the generation of the route and the generation of the driving control signal. For example, the vehicle 100 may acquire the detection result of the internal sensor and reflect the detection result of the internal sensor in the route when generating the route. The vehicle 100 may acquire the detection result of the internal sensor and reflect the detection result of the internal sensor in the driving control signal when generating the driving control signal.

[0058] (C4) In the above-described first embodiment, the server 200 automatically generates the driving control signal to be transmitted to the vehicle 100. In contrast, the server 200 may generate the driving control signal to be transmitted to the vehicle 100 according to the operation of an external operator located outside the vehicle 100. For example, an external operator operates a control device including a display for displaying a captured image output from an external sensor, a steering wheel for remotely operating the vehicle 100, an accelerator pedal, a brake pedal, and a communication device for communicating with the server 200 by wire or wireless communication, and the server 200 may generate a driving control signal corresponding to the operation applied to the control device.

[0059] (C5) In each of the above embodiments, the vehicle 100 may be configured to be movable by autonomous driving. For example, it may be in the form of a platform having the following configuration. Specifically, the vehicle 100 may include at least a control device for controlling the running of the vehicle 100 and an actuator of the vehicle 100 in order to exhibit the three functions of "running", "turning", and "stopping" by autonomous driving. When the vehicle 100 acquires information from the outside for autonomous driving, the vehicle 100 may further include a communication device. That is, the vehicle 100 that can be moved by autonomous driving may not have at least a part of the interior parts such as a driver's seat and a dashboard, may not have at least a part of the exterior parts such as a bumper and a fender, and may not have a body shell. In this case, the remaining parts such as the body shell may be mounted on the vehicle 100 before the vehicle 100 is shipped from the factory, or the remaining parts such as the body shell may be mounted on the vehicle 100 after the vehicle 100 is shipped from the factory in a state where the remaining parts such as the body shell are not mounted on the vehicle 100. Each part may be mounted from any direction such as the upper side, lower side, front side, rear side, right side, or left side of the vehicle 100, and they may be mounted from the same direction or from different directions. Note that the positioning can be performed in the same manner as the vehicle 100 in the first embodiment for the form of the platform.

[0060] (C6) The vehicle 100 may be manufactured by combining a plurality of modules. A module means a unit composed of a plurality of parts grouped according to the parts and functions of the vehicle 100. For example, the platform of the vehicle 100 may be manufactured by combining a front module that constitutes the front part of the platform, a center module that constitutes the central part of the platform, and a rear module that constitutes the rear part of the platform. Note that the number of modules constituting the platform is not limited to three, and may be two or less or four or more. In addition to, or instead of, the parts constituting the platform, parts constituting a portion of the vehicle 100 different from the platform may be modularized. Also, each type of module may include any exterior parts such as bumpers and grills, and any interior parts such as seats and consoles. Further, not limited to the vehicle 100, any type of moving body may be manufactured by combining a plurality of modules. Such modules may be manufactured, for example, by joining a plurality of parts by welding or fixtures, or by integrally molding at least a part of the parts constituting the module by casting as one part. The molding method of integrally molding one part, particularly a relatively large part, is also called gigacasting or megacasting. For example, the above-mentioned front module, center module, and rear module may be manufactured using gigacasting.

[0061] (C7) Using the running of the vehicle 100 by autonomous driving to transport the vehicle 100 is also called "self-propelled transport". Also, the configuration for realizing self-propelled transport is also called "vehicle remote control autonomous driving transport system". Further, the production method of producing the vehicle 100 using self-propelled transport is also called "self-propelled production". In self-propelled production, for example, in a factory that manufactures the vehicle 100, at least a part of the transport of the vehicle 100 is realized by self-propelled transport.

[0062] The present disclosure is not limited to the above-described embodiments, and can be implemented in various configurations without departing from the gist thereof. For example, the technical features in the embodiments corresponding to the technical features in each form described in the summary of the invention can be appropriately replaced or combined in order to solve some or all of the above-described problems, or to achieve some or all of the above-described effects. Further, if the technical feature is not described as essential in this specification, it can be appropriately deleted.

Explanation of Reference Numerals

[0063] 10…Remote control system, 100…Vehicle, 110…Vehicle control device, 111…Processor, 112…Memory, 113…Input / output interface, 114…Internal bus, 115…Vehicle control unit, 116…Position information acquisition unit, 120…Actuator group, 121…Three-dimensional point cloud data acquisition unit, 122…Range specification unit, 123…Estimation unit, 124…Control command generation unit, 130…Communication device, 140…GPS receiver, 150…Communication device, 200…Remote control device (server), 201…Processor, 202…Memory, 203…Input / output interface, 204…Internal bus, 205…Communication device, 210…Three-dimensional point cloud data acquisition unit, 220…Range specification unit, 230…Estimation unit, 240…Remote control command generation unit, 300…Distance measuring device (external sensor), 400…Process management device

Claims

A control device that generates a control command for controlling the moving body using the three-dimensional point cloud data of the moving body measured by LiDAR, comprising: A range specifying unit that specifies a use range that is a range including only a part of the three-dimensional point cloud data; An estimation unit that estimates at least one of the position and orientation of the moving body using the three-dimensional point cloud data of the use range; Comprising; The use range is specified to include a characteristic part determined according to the type of the moving body, the control device.

2. The control device according to claim 1, wherein: The range specifying unit executes a process of specifying the use range when the processing load of the control device is greater than a preset reference value, and does not execute a process of specifying the use range when the processing load is less than or equal to the reference value, the control device.

3. A method for controlling a moving body, comprising: (a) A step of acquiring the three-dimensional point cloud data of the moving body measured by LiDAR; (b) A step of specifying a use range that is a range including only a part of the three-dimensional point cloud data; (c) A step of estimating at least one of the position and orientation of the moving body using the three-dimensional point cloud data of the use range; (d) A step of generating a control command for controlling the moving body using at least one of the position and orientation of the moving body; Including; The use range is specified to include a characteristic part determined according to the type of the moving body, the control method.

4. A system for controlling a moving body, comprising: LiDAR that measures the three-dimensional point cloud data of the moving body; A control device that generates a control command for controlling the moving body using the three-dimensional point cloud data; Comprising; The control device is: A range specifying unit that specifies a use range that is a range including only a part of the three-dimensional point cloud data; An estimation unit that estimates at least one of the position and orientation of the moving body using the three-dimensional point cloud data of the use range; Including; The use range is specified to include a characteristic part determined according to the type of the moving body, the system.

5. A control device that generates a control command for controlling the moving body using the three-dimensional point cloud data of the moving body measured by LiDAR, comprising: A range specifying unit that specifies a use range that is a range including only a part of the three-dimensional point cloud data; An estimation unit that estimates at least one of the position and orientation of the moving body using the three-dimensional point cloud data within the usage range; comprising; The usage range is specified to include a characteristic portion where the density of the point cloud is higher than the average value in the observation region, among the observation regions of the moving body that can be observed by the LiDAR, a control device.

6. A method for controlling a moving body, comprising: (a) obtaining three-dimensional point cloud data of the moving body measured using a LiDAR; (b) specifying a usage range that is a range including only a part of the three-dimensional point cloud data; (c) estimating at least one of the position and orientation of the moving body using the three-dimensional point cloud data within the usage range; (d) generating a control command for controlling the moving body using at least one of the position and orientation of the moving body; including; The usage range is specified to include a characteristic portion where the density of the point cloud is higher than the average value in the observation region, among the observation regions of the moving body that can be observed by the LiDAR, a control method.

7. A system for controlling a moving body, comprising: a LiDAR that measures three-dimensional point cloud data of the moving body; a control device that generates a control command for controlling the moving body using the three-dimensional point cloud data; comprising; The control device includes: a range specifying unit that specifies a usage range that is a range including only a part of the three-dimensional point cloud data; an estimation unit that estimates at least one of the position and orientation of the moving body using the three-dimensional point cloud data within the usage range; including; The usage range is specified to include a characteristic portion where the density of the point cloud is higher than the average value in the observation region, among the observation regions of the moving body that can be observed by the LiDAR, a system.

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