Device and method

Abstract

To suppress a long time required to estimate a position and an orientation of a moving object.SOLUTION: A device comprises: an existence range determination unit that uses positional information of a moving object movable by unmanned operation to determine an existence range which includes at least a range in which the moving object is located within a measurable possible range of a distance measuring device; and an estimation unit that estimates at least one of a position and an orientation of the moving object using a measurement result of an existence range determined by the existence range determination unit using the distance measuring device.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present disclosure relates to an apparatus and a method for estimating at least one of the position and orientation of a moving object.

Background Art

[0002] In the manufacturing process of vehicles, a technology for driving a vehicle by autonomous driving 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 object such as a vehicle by autonomous driving, a process of estimating the position and orientation of the moving object is executed. The position and orientation of the moving object can be estimated using measurement results obtained from a distance measuring device such as LiDAR (Light Detection and Ranging). However, if the measurement results contain a lot of information about objects other than the moving object, the time required to estimate the position and orientation of the moving object will be prolonged.

Means for Solving the Problems

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

[0006] (1) According to a first aspect of the present disclosure, an apparatus is provided. The apparatus includes an existence range determination unit that determines an existence range including at least a range where the moving object is located from among measurable ranges of a distance measuring device using position information of a moving object movable by autonomous driving, and an estimation unit that estimates at least one of the position and orientation of the moving object using measurement results of the existence range determined by the existence range determination unit by the distance measuring device. According to the device of this form, in order to estimate at least one of the position and orientation of the moving object using the measurement result of the existence range, it is possible to suppress the extension of the time for estimating at least one of the position and orientation of the moving object. (2) In the device of the above form, when the existence range determination unit determines that an obstacle is located between the distance measuring device and the moving object, the existence range may be determined as a range obtained by removing the range hidden by the obstacle from the range where the moving object is located. According to the device of this form, since the existence range is determined by excluding the range hidden by the obstacle, it is possible to suppress a decrease in the estimation accuracy of at least one of the position and orientation of the moving object due to the obstacle. (3) In the device of the above form, the moving object moves in the factory where the moving object is manufactured, and the existence range determination unit may determine whether or not the obstacle is located between the distance measuring device and the moving object using information related to the manufacturing process of the moving object. According to the device of this form, it is possible to easily determine whether or not an obstacle is located between the distance measuring device and the moving object. (4) In the device of the above form, the existence range determination unit may determine whether or not the obstacle is located between the distance measuring device and the moving object using the weather information of the place where the moving object is located. According to the device of this form, it is possible to easily determine whether or not an obstacle is located between the distance measuring device and the moving object. (5) According to the second form of the present disclosure, a method is provided. This method determines an existence range including at least the range where the moving object is located from the measurable range of the distance measuring device using the position information of the moving object that can be moved by unmanned driving, and estimates at least one of the position and orientation of the moving object using the measurement result of the determined existence range by the distance measuring device. According to the method of this form, in order to estimate at least one of the position and orientation of the moving object using the measurement result of the existence range, it is possible to suppress the extension of the time for estimating at least one of the position and orientation of the moving object. The present disclosure can also be implemented in various forms other than apparatuses and methods. For example, it can be implemented in the form of a system, a computer program, and a recording medium on which the computer program is recorded.

Brief Description of the Drawings

[0007]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Modes for Carrying Out the Invention

[0008] A. First Embodiment: FIG. 1 is an explanatory diagram showing the configuration of a system 10 according to the first embodiment. The system 10 includes a vehicle 100, a server device 200, a first sensor 301, a second sensor 302, and a process management device 400. In the present embodiment, the vehicle 100 corresponds to the "moving body" of the present disclosure, and the server device 200 corresponds to the "device" of the present disclosure.

[0009] In the present disclosure, a "mobile body" means an object that can move, such as a vehicle or an electric vertical takeoff and landing aircraft (so-called flying car). The vehicle may be a vehicle that travels on wheels or a vehicle that travels on an endless track, such as a passenger car, a truck, a bus, a two-wheeled vehicle, a four-wheeled vehicle, a tank, a construction vehicle, etc. The vehicle includes battery electric vehicles (BEVs), gasoline vehicles, hybrid vehicles, and fuel cell vehicles. 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".

[0010] The vehicle 100 is configured to be capable of traveling by autonomous driving. "Autonomous driving" means driving without depending on the driving operation of a passenger. The driving operation means an operation related to at least any one of "running", "turning", and "stopping" of the vehicle 100. Autonomous driving is realized by automatic or manual remote control using a device located outside the vehicle 100, or by autonomous control of the vehicle 100. A passenger who does not perform a driving operation may board the vehicle 100 traveling by autonomous driving. Passengers who do not perform a driving operation include, for example, a person simply sitting on the seat of the vehicle 100, or a person performing work different from the driving operation, such as assembly, inspection, and operation of switches, while boarding the vehicle 100. Note that driving by the driving operation of a passenger is sometimes called "manned driving".

[0011] In this specification, "remote control" includes "complete remote control" in which all of the operations of the vehicle 100 are completely determined from outside the vehicle 100, and "partial remote control" in which a part of the operations of the vehicle 100 is determined from outside the vehicle 100. Also, "autonomous control" includes "complete autonomous control" in which the vehicle 100 autonomously controls its own operations without receiving any information from a device outside the vehicle 100, and "partial autonomous control" in which the vehicle 100 autonomously controls its own operations using information received from a device outside the vehicle 100.

[0012] In this embodiment, remote control of the vehicle 100 is performed at the factory FC that manufactures the vehicle 100. The factory FC includes a first location PL1 and a second location PL2. The first location PL1 and the second location PL2 are connected by a road TR on which the vehicle 100 can travel. The first location PL1 is, for example, a location where the vehicle 100 is assembled, and the second location PL2 is, for example, a location where the vehicle 100 is inspected.

[0013] A plurality of first sensors 301 and a plurality of second sensors 302 for measuring individual vehicles 100 are installed around the road TR. In this embodiment, the first sensor 301 is a camera, and the second sensor 302 is a LiDAR (Light Detection And Ranging). The first sensor 301 and the second sensor 302 are provided with a communication device (not shown) and can communicate with the server device 200 by wired communication or wireless communication. The server device 200 can estimate the relative position and orientation of the vehicle 100 with respect to the reference path RR in real time using the first sensor 301 and the second sensor 302. The positions and orientations of the individual first sensors 301 and the individual second sensors 302 are fixed, and the relative relationships between the reference coordinate system Σr of the factory FC, the coordinate system of the individual first sensors 301, and the coordinate system of the individual second sensors 302 are known. The first sensor 301 and the second sensor 302 are preferably arranged side by side vertically or horizontally so as to measure the vehicle 100 in the same orientation. A coordinate transformation matrix for mutually transforming the coordinate values of the reference coordinate system Σr, the coordinate values of the coordinate system of the individual first sensors 301, and the coordinate values of the coordinate system of the individual second sensors 302 is stored in advance in the server device 200.

[0014] The server device 200 generates a driving control signal for driving the vehicle 100 along the reference path RR and transmits the driving control signal to the vehicle 100. The vehicle 100 travels according to the received driving control signal. Therefore, according to the system 10, the vehicle 100 can be moved from the first location PL1 to the second location PL2 by remote control without using a conveying device such as a crane or a conveyor.

[0015] The process management device 400 executes overall management of the manufacturing process of the vehicle 100 in the factory FC. The process management device 400 is composed of at least one computer. The process management device 400 has a database in which various information related to the manufacturing process of the vehicle 100 is recorded. The various information recorded in the database includes, for example, the identification number of the vehicle 100, the vehicle type, the content of the manufacturing process, and information regarding the progress of the manufacturing process. The process management device 400 is provided with a communication device (not shown) and can communicate with the server device 200 by wired communication or wireless communication.

[0016] FIG. 2 is a block diagram showing the configuration of the system 10 in the present embodiment. In the present embodiment, the vehicle 100 is configured to be capable of traveling by remote control. The vehicle 100 includes a vehicle control device 110 for controlling each part of the vehicle 100, an actuator group 120 including at least one actuator that drives under the control of the vehicle control device 110, and a communication device 130 for communicating with the server device 200 by wireless communication. 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 wheels rotated by the traveling motor. The actuator of the driving device includes the traveling motor.

[0017] The vehicle control device 110 is composed of 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 and the communication device 130 are connected to the input / output interface 113.

[0018] The processor 111 functions as a travel control unit 115 by executing a computer program PG1 prestored in the memory 112. The travel control unit 115 controls the actuator group 120. When a passenger is on board the vehicle 100, the travel control unit 115 can drive the vehicle 100 by controlling the actuator group 120 according to the operation of the passenger. Regardless of whether a passenger is on board the vehicle 100 or not, the travel control unit 115 can drive the vehicle 100 by controlling the actuator group 120 according to the travel control signal received from the server device 200. The travel control signal is a control signal for driving the vehicle 100. In the present embodiment, the travel control signal includes the acceleration and the steering angle of the vehicle 100 as parameters. In other embodiments, the travel control signal may include the speed of the vehicle 100 as a parameter instead of, or in addition to, the acceleration of the vehicle 100.

[0019] The server device 200 is configured 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 to be communicable bidirectionally via the internal bus 204. A communication device 205 for communicating with the vehicle 100 by wireless communication is connected to the input / output interface 203. In the present embodiment, the communication device 205 can further communicate with the first sensor 301, the second sensor 302, and the process management device 400 by wire communication or wireless communication.

[0020] The processor 201 functions as a position information acquisition unit 210, an existence range determination unit 220, a measurement result acquisition unit 230, an estimation unit 240, and a remote control unit 250 by executing a computer program PG2 prestored in the memory 202.

[0021] The position information acquisition unit 210 acquires position information indicating the approximate position of the vehicle 100 using the measurement result of the first sensor 301. The approximate position of the vehicle 100 refers to the general position of the vehicle 100. In the present embodiment, the first sensor 301 is a camera located outside the vehicle 100. The position information acquisition unit 210 acquires position information indicating the approximate position of the vehicle 100 using the captured image of the camera. Note that in other embodiments, the first sensor 301 may be a sonar located outside the vehicle 100. In this case, the position information acquisition unit 210 may acquire position information indicating the approximate position of the vehicle 100 using the measurement result of the sonar. Further, the first sensor 301 may be a GPS sensor mounted on the vehicle 100. In this case, the position information acquisition unit 210 may acquire position information indicating the approximate position of the vehicle 100 from the GPS sensor.

[0022] The existence range determination unit 220 determines an existence range UR that includes at least the range where the vehicle 100 is located from among the measurable ranges of the second sensor 302 using the position information indicating the approximate position of the vehicle 100. The existence range UR is preferably the range where the vehicle 100 actually exists, but may also be the range where the vehicle 100 is presumed to exist. In the present embodiment, the second sensor 302 is a LiDAR located outside the vehicle 100. The second sensor 302 is controlled to measure a preset measurement range MR within the measurable range. Note that in other embodiments, the second sensor 302 may be a ranging device other than LiDAR such as a camera.

[0023] The measurement result acquisition unit 230 acquires the measurement result of the existence range UR by the second sensor 302. In the present embodiment, the measurement result of the existence range UR is acquired by extracting the measurement result of the existence range UR from the measurement result of the measurement range MR acquired from the second sensor 302. Note that when the measurement range MR of the second sensor 302 can be changed, the measurement result acquisition unit 230 may acquire the measurement result of the existence range UR from the second sensor 302 by limiting the measurement range MR of the second sensor 302 to the existence range UR.

[0024] The estimation unit 240 estimates at least one of the position and orientation of the vehicle 100 using the measurement result of the presence range UR by the second sensor 302. In the present embodiment, the estimation unit 240 estimates both the position and orientation of the vehicle 100. Note that, in other embodiments, the estimation unit 240 may estimate only one of the position and orientation of the vehicle 100.

[0025] The remote control unit 250 generates a driving control signal for driving the vehicle 100 using the estimation result of the estimation unit 240, and transmits the generated driving control signal to the vehicle 100.

[0026] FIG. 3 is a flowchart showing the processing procedure of the driving control of the vehicle 100 in the first embodiment. In step S1, the remote control unit 250 acquires vehicle position information. The vehicle position information is the position information that serves as the basis for generating the driving control signal. In the present embodiment, the vehicle position information includes the position and orientation of the vehicle 100 in the reference coordinate system Σr of the factory FC. In the following description, the reference coordinate system Σr of the factory FC is referred to as the global coordinate system. Any position within the factory FC is represented by the coordinates of X, Y, and Z in the global coordinate system. Details of the method for acquiring the vehicle position information will be described later.

[0027] In step S2, the remote control unit 250 determines the target position to which the vehicle 100 should next head. In the present embodiment, the target position is represented by the coordinates of X, Y, and Z in the global coordinate system. In the memory 202 of the server device 200, a reference route RR, which is the route along which the vehicle 100 should travel, is stored in advance. The route is represented by a node indicating the departure point, a node indicating the passing point, a node indicating the destination, and links connecting each node. The remote control unit 250 determines the target position to which the vehicle 100 should next head using the vehicle position information and the reference route RR. The remote control unit 250 determines the target position on the reference route RR ahead of the current position of the vehicle 100.

[0028] In step S3, the remote control unit 250 generates a driving control signal for driving the vehicle 100 toward the determined target position. In the present embodiment, the driving control signal includes the acceleration and steering angle of the vehicle 100 as parameters. In other embodiments, the driving control signal may include the speed of the vehicle 100 as a parameter instead of, or in addition to, the acceleration of the vehicle 100. The remote control unit 250 calculates the driving speed of the vehicle 100 from the change in the position of the vehicle 100 and compares the calculated driving speed with the target speed. Overall, when the driving speed is lower than the target speed, the remote control unit 250 determines the acceleration so that the vehicle 100 accelerates, and when the driving speed is higher than the target speed, the remote control unit 250 determines the acceleration so that the vehicle 100 decelerates. Further, when the vehicle 100 is located on the reference path RR, the remote control unit 250 determines the steering angle and acceleration so that the vehicle 100 does not deviate from the reference path RR, and when the vehicle 100 is not located on the reference path RR, in other words, when the vehicle 100 has deviated from the reference path RR, the remote control unit 250 determines the steering angle and acceleration so that the vehicle 100 returns to the reference path RR.

[0029] In step S4, the remote control unit 250 transmits the generated driving control signal to the vehicle 100. The remote control unit 250 repeats the acquisition of the position of the vehicle 100, determination of the target position, generation of the driving control signal, and transmission of the driving control signal, etc. at a predetermined cycle.

[0030] In step S5, the driving control unit 115 of the vehicle 100 receives the driving control signal transmitted from the server device 200. In step S6, the driving control unit 115 controls the actuator group 120 using the received driving control signal, and drives the vehicle 100 at the acceleration and steering angle represented by the driving control signal. The driving control unit 115 repeats the reception of the driving control signal and the control of the actuator group 120 at a predetermined cycle.

[0031] FIG. 4 is a flowchart showing a processing procedure for estimating the position and orientation of the vehicle 100 in the present embodiment. FIG. 5 is an explanatory diagram showing the existence range UR in the present embodiment. The process shown in FIG. 4 is executed by the processor 201 of the server device 200 in step S1 shown in FIG. 3. In step S110, the position information acquisition unit 210 acquires the measurement result of the first sensor 301. In the present embodiment, the first sensor 301 is a camera. The position information acquisition unit 210 acquires a captured image as the measurement result of the first sensor 301. The vehicle 100 is represented in the captured image.

[0032] In step S120, the position information acquisition unit 210 acquires the approximate position of the vehicle 100 using the captured image. The approximate position of the vehicle 100 is represented by, for example, the coordinate values of the eight vertices of a rectangular parallelepiped including the vehicle 100. The position information acquisition unit 210 detects the outer shape of the vehicle 100 from the captured image, calculates the coordinate values of the eight vertices in the device coordinate system of the first sensor 301, that is, the local coordinate system with respect to the global coordinate system, and converts the calculated coordinate values into the coordinate values in the global coordinate system, thereby acquiring the approximate 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 stored in advance in the memory 202 of the server device 200. Examples of the detection model include a trained 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).

[0033] In step S130, the existence range determination unit 220 determines an existence range UR from within the measurable range of the second sensor 302 according to the approximate position of the vehicle 100. As shown in FIG. 5, in this embodiment, the existence range determination unit 220 determines the existence range UR so as to include the entire vehicle 100. The existence range determination unit 220 determines the range surrounded by the above-described rectangular parallelepiped as the existence range UR. In this embodiment, the measurable range of the second sensor 302 is a 360-degree range along the horizontal plane centered on the second sensor 302. The second sensor 302 is controlled to measure a preset measurement range MR within the measurable range. The measurement range MR is set to a range in which the vehicle 100 is assumed to travel. The existence range UR is determined so as to be included in the measurement range MR.

[0034] In step S140, the measurement result acquisition unit 230 acquires the measurement result of the second sensor 302. In this embodiment, the second sensor 302 is a LiDAR. The measurement result acquisition unit 230 acquires a three-dimensional point cloud as the measurement result of the second sensor 302. In this embodiment, the second sensor 302 measures a preset measurement range MR. In the following description, the three-dimensional point cloud included in the measurement result of the second sensor 302 is referred to as a measurement point cloud. The measurement point cloud may include, in addition to the point cloud obtained by measuring the vehicle 100, the point cloud obtained by measuring the travel path TR, and the point cloud obtained by measuring various facilities of the factory FC arranged around the travel path TR. The measurement result acquisition unit 230 acquires the measurement point cloud of the existence range UR by extracting the portion of the existence range UR from the entire measurement point cloud.

[0035] In step S150, the estimation unit 240 estimates the position and orientation of the vehicle 100 using the measurement point group within the existence range UR. In the present embodiment, the estimation unit 240 estimates the position and orientation of the vehicle 100 by point cloud matching using the measurement point group of the existence range UR and the reference point group RT, and generates vehicle position information as the estimation result of the position and orientation of the vehicle 100. As a method of point cloud matching, for example, NDT (Normal Distributions Transform) or ICP (Iterative Closest Point) can be used. Thereafter, the processor 201 ends this process and proceeds to step S2 shown in FIG. 3.

[0036] According to the server device 200 in the present embodiment described above, the existence range UR is determined according to the approximate position of the vehicle 100, and the position and orientation of the vehicle 100 are estimated using the measurement point group within the existence range UR. Generally, estimating the position and orientation of the vehicle 100 using the measurement point group of LiDAR can estimate the position and orientation of the vehicle 100 more accurately than estimating the position and orientation of the vehicle 100 using the captured image of the camera. However, if the measurement point group used for point cloud matching contains many point clouds other than the vehicle 100, the time required to estimate the position and orientation of the vehicle 100 may be prolonged. For example, in a large place such as a yard, since the range in which the vehicle 100 can travel is wide, it is preferable to set the measurement range MR of the second sensor 302 wide. However, when the measurement range MR of the second sensor 302 is set wide, the measurement point group used for point cloud matching tends to contain many point clouds other than the vehicle 100. On the other hand, in the present embodiment, since the server device 200 executes point cloud matching using the measurement point group within the existence range UR, the number of point clouds other than the vehicle 100 included in the measurement point group used for point cloud matching can be reduced. Therefore, it is possible to suppress the time required to estimate the position and orientation of the vehicle 100 from being prolonged.

[0037] Also, in the present embodiment, the measurement result acquisition unit 230 extracts the measurement point group within the existence range UR used for point cloud matching from the measurement point group acquired from the second sensor 302. Therefore, even without changing the measurement range MR of the second sensor 302, the measurement point group within the existence range UR can be acquired.

[0038] Also, in the present embodiment, the position information acquisition unit 210 acquires the coordinate values of the eight vertices of the rectangular parallelepiped surrounding the vehicle 100 as the position information indicating the approximate position of the vehicle 100. Therefore, the range where the vehicle 100 exists can be easily expressed. In other embodiments, the position information acquisition unit 210 may calculate the coordinate values of a predetermined measurement point of the vehicle 100 instead of acquiring the coordinate values of the vertices of the rectangular parallelepiped including the vehicle 100. In this case, even if a problem occurs in the estimation of the position of the vehicle 100 using the measurement result of the second sensor 302, the travel control signal of the vehicle 100 can be generated using the coordinate values of the measurement points acquired by the position information acquisition unit 210, so the redundancy of the system 10 can be increased.

[0039] B. Second Embodiment: FIG. 6 is a flowchart showing the processing procedure for estimating the position and orientation of the vehicle 100 in the second embodiment. FIG. 7 is an explanatory diagram showing the existence range UR in the second embodiment. In the present embodiment, the method for determining the existence range UR is different from that in the first embodiment. For other configurations, they are the same as those in the first embodiment unless otherwise specified.

[0040] The processing from step S210 to step S220 shown in FIG. 6 is the same as the processing from step S110 to step S120 shown in FIG. 4. In step S210, the position information acquisition unit 210 acquires the captured image of the camera which is the first sensor 301. In step S220, the position information acquisition unit 210 acquires the position information indicating the approximate position of the vehicle 100 using the captured image.

[0041] In this embodiment, after step S220, in step S230, the existence range determination unit 220 determines whether a part of the vehicle 100 is hidden by the obstacle OB. In FIG. 7, a worker is illustrated as the obstacle OB. In addition to the worker being the obstacle OB, for example, various facilities in the factory FC such as a robot arm that assembles parts to the vehicle 100 can be the obstacle OB. In this embodiment, the existence range determination unit 220 determines whether a part of the vehicle 100 is hidden by the obstacle OB by analyzing the captured image of the first sensor 301. The existence range determination unit 220 can detect the obstacle OB, for example, by inputting the captured image into a detection model that utilizes artificial intelligence.

[0042] If it is not determined in step S230 that a part of the vehicle 100 is hidden by the obstacle OB, then in step S232, the existence range determination unit 220 determines the existence range UR so as to include the entire vehicle 100. On the other hand, if it is determined in step S230 that a part of the vehicle 100 is hidden by the obstacle OB, then in step S235, the existence range determination unit 220 determines the existence range UR so as to include a part of the vehicle 100 from which the portion hidden by the obstacle OB is excluded from the entire vehicle 100.

[0043] The processing from step S240 to step S250 is the same as the processing from step S140 to step S150 shown in FIG. 4. In step S240, the measurement result acquisition unit 230 acquires the measurement point group of the existence range UR. In step S250, the estimation unit 240 estimates the position and orientation of the vehicle 100 by point cloud matching using the reference point group RT and the measurement point group of the existence range UR.

[0044] According to the system 10 in this embodiment described above, when an obstacle OB is interposed between the second sensor 302 and the vehicle, the existence range determination unit 220 determines the existence range UR by excluding the range hidden by the obstacle OB. Therefore, it is possible to suppress a decrease in the estimation accuracy of the position and orientation of the vehicle 100 due to the interposition of the obstacle OB between the second sensor 302 and the vehicle 100.

[0045] In other embodiments, in step S230, the existence range determination unit 220 may obtain information related to the manufacturing process from the process management device 400 and determine whether a part of the vehicle 100 is hidden by the obstacle OB using the information related to the manufacturing process. For example, when the current manufacturing process of the vehicle 100 is a process of attaching a front fender to the front end of the vehicle 100, the front end of the vehicle 100 is likely to be hidden by the operator. Therefore, when the current manufacturing process of the vehicle 100 is a process of attaching a front fender to the front end of the vehicle 100, the existence range determination unit 220 may determine in step S230 that a part of the vehicle 100 is hidden by the obstacle OB, and in step S235, determine the existence range UR so that the part of the vehicle 100 excluding the front end hidden by the operator from the whole vehicle 100 is included. When the manufacturing process of the vehicle 100 is associated with the reference route RR, the manufacturing process of the vehicle 100 may be determined from the current location on the reference route RR of the vehicle 100.

[0046] In other embodiments, in step S230, the existence range determination unit 220 may obtain weather information from the process management device 400 or outside the system 10 and determine whether a part of the vehicle 100 is hidden by the obstacle OB using the weather information. For example, in autumn and winter, fallen leaves and snow are likely to accumulate on the outdoor runway TR, so there is a high possibility that the lower part of the vehicle 100, especially the part below the rotation axis of the wheels, is hidden by the accumulated fallen leaves and snow. Therefore, when it is estimated using the weather information that it is a season when fallen leaves are likely to accumulate or a weather when snow is likely to accumulate, the existence range determination unit 220 may determine in step S230 that a part of the vehicle 100 is hidden by the obstacle OB, and in step S235, determine the existence range UR so that the part of the vehicle 100 excluding the part below the rotation axis of the wheels that is likely to be hidden by fallen leaves and snow from the whole vehicle 100 is included.

[0047] C. Third Embodiment: FIG. 8 is a block diagram showing the configuration of the system 10c in the third embodiment. In this embodiment, the system 10c is different from the first embodiment in that it does not include the server device 200 and the vehicle 100 travels by autonomous control instead of remote control. For other configurations, unless otherwise specified, they are the same as those in the first embodiment.

[0048] In this embodiment, the vehicle 100 is configured to be capable of traveling by autonomous control. The vehicle 100 can communicate with the first sensor 301, the second sensor 302, and the process management device 400 by wireless communication using the communication device 130. In the memory 112, a computer program PG1, a reference point group RT, and a reference route RR are stored in advance. The reference point group RT is a three-dimensional point group representing the appearance of the vehicle 100. The reference point group RT can be created using, for example, three-dimensional CAD data or three-dimensional CG data representing the appearance of the vehicle 100. In this embodiment, the processor 111 functions as a position information acquisition unit 191, an existence range determination unit 192, a measurement result acquisition unit 193, an estimation unit 194, and a travel control unit 115c by executing the computer program PG1 stored in advance in the memory 112. The functions of the position information acquisition unit 191, the existence range determination unit 192, the measurement result acquisition unit 193, and the estimation unit 194 are the same as the functions of the position information acquisition unit 210, the existence range determination unit 220, the measurement result acquisition unit 230, and the estimation unit 240 of the server device 200 in the first embodiment shown in FIG. 2. In this embodiment, the travel control unit 115c generates a travel control signal by itself according to the estimation result of the estimation unit 194, and controls the actuator group 120 using the generated travel control signal to cause the vehicle 100 to travel.

[0049] FIG. 9 is a flowchart showing the processing procedure of the travel control of the vehicle 100 in the present embodiment. In step S11, the travel control unit 115c acquires the vehicle position information which is the estimation result of the estimation unit 194. In step S21, the travel control unit 115c determines the target position to which the vehicle 100 should next head. In step S31, the travel control unit 115c generates a travel control signal for causing the vehicle 100 to travel toward the determined target position. In step S41, the travel control unit 115c controls the actuator group 120 using the generated travel control signal, thereby causing the vehicle 100 to travel according to the parameters represented by the travel control signal. The travel control unit 115c repeats the acquisition of the vehicle position information, the determination of the target position, the generation of the travel control signal, and the control of the actuator group 120 at a predetermined cycle.

[0050] In the present embodiment described above, the vehicle 100 can be caused to travel by the autonomous control of the vehicle 100 without remotely controlling the vehicle 100 by the server device 200.

[0051] D. Other Embodiments: (D1) In the first to second embodiments described above, the server device 200 executes the processing from the acquisition of the vehicle position information to the generation of the travel control signal. On the other hand, as another embodiment D1, at least a part of the processing from the acquisition of the vehicle position information to the generation of the travel control signal may be executed by the vehicle 100. For example, the following forms (1) to (3) may be used.

[0052] (1) The server device 200 may acquire the vehicle position information, determine the target position to which the vehicle 100 should next head, and generate a route from the current position of the vehicle 100 represented by the acquired vehicle position information to the target position. The server device 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 device 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 device 200, and control the actuator group 120 using the generated travel control signal.

[0053] (2) The server device 200 may acquire vehicle position information and transmit the acquired vehicle position information to the vehicle 100. The vehicle 100 may determine the target position to which the vehicle 100 should next head, generate a route from the current position of the vehicle 100 represented by the received vehicle position information to the target position, generate a driving control signal so that the vehicle 100 travels on the generated route, and control the actuator group 120 using the generated driving control signal.

[0054] (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. The internal sensor may include, for example, a sensor that detects the motion state of the vehicle 100, a sensor that detects the operation state of each part of the vehicle 100, or a sensor that detects the environment around 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 device 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.

[0055] (D2) In another embodiment D2, in the above-described third embodiment, the vehicle 100 is equipped with an internal sensor, 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.

[0056] (D3) In the above-described third embodiment, the vehicle 100 acquires vehicle position information using the measurement results of a camera or LiDAR located outside the vehicle 100. In contrast, in another embodiment D3, the vehicle 100 is equipped with an internal sensor, and the vehicle 100 acquires vehicle position information using the detection result of the internal sensor, determines the target position to which the vehicle 100 should next head, generates a route from the current position of the vehicle 100 represented in the acquired vehicle position information to the target position, generates a driving control signal for driving along the generated route, and may control the actuator group 120 using the generated driving control signal. In this case, the vehicle 100 can travel without using the measurement results of the first sensor 301 or the second sensor 302 at all. Note that the vehicle 100 may acquire the target arrival time and traffic jam information from outside the vehicle 100 and reflect the target arrival time and traffic jam information in at least one of the route and the driving control signal.

[0057] (D4) In the above first to second embodiments, the server device 200 automatically generates a driving control signal to be transmitted to the vehicle 100. In contrast, as another embodiment D4, the server device 200 may generate a 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 imaging image output from a camera which is the first sensor 301, a display for displaying a three-dimensional point cloud output from a LiDAR which is the second sensor 302, a steering wheel for remotely operating the vehicle 100, an accelerator pedal, a brake pedal, and a control device including a communication device for communicating with the server device 200 by wired communication or wireless communication are operated by an external operator, and the server device 200 may generate a driving control signal corresponding to the operation applied to the control device.

[0058] In the above-described first to third embodiments and other embodiments D1 to D4, the vehicle 100 only needs to be configured to be movable by autonomous driving. For example, it may be in the form of a platform having the following-described configuration. Specifically, the vehicle 100 only needs to include at least the vehicle control device 110 and the actuator group 120 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 the communication device 130. 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 the driver's seat and the dashboard, and may not have at least a part of the exterior parts such as the bumper and the fender, and may not have the body shell mounted thereon. In this case, until the vehicle 100 is shipped from the factory FC, the remaining parts such as the body shell may be mounted on the vehicle 100, or the vehicle 100 may be shipped from the factory FC in a state where the remaining parts such as the body shell are not mounted on the vehicle 100, and then the remaining parts such as the body shell may be mounted on the vehicle 100. Each part may be mounted from any direction such as the upper side, the lower side, the front side, the rear side, the right side, or the left side of the vehicle 100, and they may be mounted from the same direction or from different directions respectively. Note that the positioning of the platform form can be performed in the same manner as the vehicle 100 in the first embodiment.

[0059] (D6) 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 or 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 central 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, the parts constituting a portion of the vehicle 100 different from the platform may be modularized. Also, various modules may include any exterior parts such as bumpers and grilles, 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, etc., or by integrally molding at least a part of the parts constituting the module by casting as a single part. The molding method of integrally molding a single part, particularly a relatively large part, is also called gigacasting or megacasting. For example, the above front module, central module, and rear module may be manufactured using gigacasting.

[0060] (D7) 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 the factory FC that manufactures the vehicle 100, at least a part of the transport of the vehicle 100 is realized by self-propelled transport.

[0061] In each of the above embodiments, part or all of the functions and processes realized software may be realized hardware. Also, part or all of the functions and processes realized hardware may be realized software. As the hardware for realizing the various functions in each of the above embodiments, for example, various circuits such as integrated circuits and discrete circuits may be used.

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

Description of Reference Numerals

[0063] 10, 10c... system, 100... vehicle, 110... vehicle control device, 111... processor, 112... memory, 113... input / output interface, 114... internal bus, 115, 115c... travel control unit, 120... actuator group, 130... communication device, 191... position information acquisition unit, 192... presence range determination unit, 193... measurement result acquisition unit, 194... estimation unit, 200... server device, 201... processor, 202... memory, 203... input / output interface, 204... internal bus, 205... communication device, 210... position information acquisition unit, 220... presence range determination unit, 230... measurement result acquisition unit, 240... estimation unit, 250... remote control unit, 301... first sensor, 302... second sensor, 400... process management device

Claims

1. An apparatus comprising: a presence range determination unit that determines a presence range including at least a range where the moving body is located from among measurable ranges of a distance measurement device using position information of a moving body movable by autonomous driving; an estimation unit that estimates at least one of a position and an orientation of the moving body using a measurement result of the presence range determined by the presence range determination unit by the distance measurement device; the apparatus.

2. The apparatus according to claim 1, wherein when the presence range determination unit determines that an obstacle is located between the distance measurement device and the moving body, the presence range determination unit determines, as the presence range, a range obtained by excluding a range hidden by the obstacle from the range where the moving body is located.

3. The apparatus according to claim 2, wherein the moving body moves in a factory that manufactures the moving body, and the presence range determination unit determines whether or not the obstacle is located between the distance measurement device and the moving body using information related to a manufacturing process of the moving body.

4. The apparatus according to claim 2, wherein the presence range determination unit determines whether or not the obstacle is located between the distance measurement device and the moving body using weather information of a location where the moving body is located.

5. A method comprising: determining a presence range including at least a range where the moving body is located from among measurable ranges of a distance measurement device using position information of a moving body movable by autonomous driving; estimating at least one of a position and an orientation of the moving body using a measurement result of the determined presence range by the distance measurement device. The method.

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