Moving body control system and moving body control method

Abstract

To provide a moving body control system and a moving body control method that are able to reduce a load when an autonomous moving body is newly introduced to a site and that are able to quickly introduce the autonomous moving body to the site.SOLUTION: A moving body control system includes: a moving destination setting unit configured to generate a moving route including a path shape and a control target; a parameter setting unit configured to set a control parameter to be used in the moving route; an information storage unit configured to store a travel record in which the path shape, the control target and the control parameter used when the moving body autonomously traveled in the past are combined. The moving body control system includes: generating past blocks obtained by dividing the route shape and the control target of the travel record; generating a set of past blocks formed by similar past blocks associated with the same control parameter; generating current blocks obtained by dividing a path shape and a control target of the moving route; comparing the path shapes and the control targets of the current blocks with the path shapes and the control targets of the set of past blocks; and generating control parameters corresponding to the set of past blocks similar to the current blocks.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a mobile object control system and a mobile object control method. [Background technology]

[0002] In order to solve the driver shortage in transporting soil at construction sites and mines, and in pick-up and drop-off services and logistics, the introduction of autonomous vehicles is progressing. The driving requirements for such autonomous vehicles vary depending on the tasks given to them. For example, when transporting people or precision machinery, the vehicle must be able to travel with minimal shaking to prevent car sickness and damage, while when transporting soil and ore, the vehicle must be able to travel round trip in a short time to increase the amount of material transported per hour. When the required driving requirements differ, the control targets (trajectory targets and target speed distributions expressed by nodes and branches / edges, etc.) given to the autonomous vehicles are different, so it becomes necessary to design control targets every time the task changes, which places a heavy burden (engineering costs) on the operation site. In addition, when the control targets differ, the controller must be adjusted to achieve the control targets. If the controller is adjusted every time the control targets change, the burden on the operation site increases even more. On the other hand, if such adjustments are not made, a general-purpose setting that can be applied to various tasks is required, which results in a decrease in control accuracy and limitations on the tasks that can be performed compared to when adjustments are made for each task.

[0003] As a conventional technique for solving such a problem, for example, the one described in Patent Document 1 is known. Patent Document 1 discloses a vehicle driving support device that outputs a target driving pattern serving as a reference for controlling the vehicle speed according to the vehicle driving state, and that, each time the vehicle travels through a section previously set on a map, classifies the vehicle based on the driving state of the vehicle, including the presence or absence of a preceding vehicle and the presence or absence of a following vehicle, stores a driving pattern indicating a change in the vehicle speed or the distance from the preceding vehicle within the section, and generates and outputs the target driving pattern based on the driving pattern classified as the same vehicle driving state as the current vehicle driving state among the stored driving patterns. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2013-193671 A Summary of the Invention [Problem to be solved by the invention]

[0005] In the above-mentioned conventional technology, a target driving pattern, which is the control target, is generated from driving patterns recorded during tasks performed by an autonomous moving body in the past, and is therefore effective in reducing the burden of repeated operations at the same site or with the same vehicle (autonomous moving body).

[0006] However, when an autonomous mobile body is newly introduced to a site, the situation is likely to be unique depending on the combination of the situation at the site, the vehicle used, the work given, etc., and it is therefore difficult to obtain a driving pattern for the same situation at the site where the autonomous mobile body is to be introduced from past records at other sites. In other words, when an autonomous mobile body is newly introduced, it is necessary to set new control targets, etc., so that the reduction in burden is limited, and it is considered that it takes time to introduce the autonomous mobile body to the site.

[0007] The present invention has been made in consideration of the above, and aims to provide a mobile object control system and a mobile object control method that can reduce the burden when introducing an autonomous mobile object to a site and enable the object to be introduced to the site quickly. [Means for solving the problem]

[0008] The present application includes multiple means for solving the above-mentioned problems. One example is a mobile body control system including a destination setting unit that determines a destination for a mobile body and generates a movement route including a route shape to the destination and a control target, a parameter setting unit that sets control parameters to be used on the movement route set by the destination setting unit, and an information storage unit that stores a driving record that records at least a combination of a route shape, a control target, and a control parameter along which the mobile body has traveled autonomously in the past. The parameter setting unit generates past blocks by dividing the route shape and control target of the driving record, generates a past block set formed of similar past blocks to which the same control parameters can be assigned, generates a current block by dividing the route shape and control target of the movement route, compares the route shape and control target of the current block with the route shape and control target of the past block set, and generates control parameters corresponding to the past block set similar to the current block. Effect of the Invention

[0009] According to the present invention, it is possible to reduce the burden when introducing an autonomous moving body to a site, and to rapidly introduce the body to the site. [Brief description of the drawings]

[0010] [Figure 1] 1 is a functional block diagram illustrating a schematic overall configuration of a mobile object control system according to a first embodiment. [Diagram 2] FIG. 1 is a diagram showing an autonomous moving body operating in a mine, which is a site of the autonomous moving body; [Diagram 3] FIG. 1 is a diagram showing a coordinate system set in a mine. [Figure 4] FIG. 2 is a functional block diagram illustrating a configuration of an autonomous moving body. [Diagram 5] FIG. 11 is a diagram showing an example of a travel route set in a travel-permitted passage; [Figure 6] FIG. 13 is a diagram showing how trajectory targets are set on a set movement route. [Figure 7]FIG. 13 is a diagram showing how a speed target is set for a set movement route. [Figure 8] FIG. 13 is a diagram showing a state in which a set movement route and a trajectory target are divided. [Figure 9] FIG. 13 is a diagram showing the state of a velocity target in each divided block. [Figure 10] FIG. 11 is a diagram showing an example of block information for each divided block. [Figure 11] FIG. 11 is a diagram illustrating an example of a relationship between block features and control parameters. [Figure 12] FIG. 10 is a diagram illustrating a method for searching for solution candidates. [Figure 13] 4 is a flowchart showing the processing contents of the mobile object control system. [Figure 14] FIG. 11 is a functional block diagram illustrating a schematic overall configuration of a mobile object control system according to a second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0012] The mobile object control system in this embodiment targets mobile objects such as autonomously operable robots and vehicles, calculates movement plans (time series of coordinates, attitude, speed, etc.) for these mobile objects, and controls the mobile objects to follow this path plan. In the following explanation, an example will be given of an autonomous vehicle operating in a mine as the autonomous mobile object to be controlled. Note that the application of the present invention is not limited to generation of movement paths for mobile objects operating in a mine, but can also be applied to, for example, generation of movement paths for transport vehicles in ports and path generation for robots moving in theme parks.

[0013] <First embodiment> A first embodiment of the present invention will be described with reference to FIGS.

[0014] FIG. 1 is a functional block diagram showing a schematic overall configuration of a mobile object control system according to the present embodiment.

[0015] In Fig. 1, the mobile object control system is generally composed of a mobile object position acquisition unit A101, a destination setting unit A102, a control information storage unit A103, a parameter setting unit A104, a control information storage unit A105, and a mobile object control unit A106. Note that, in Fig. 1, for the sake of simplicity, a case where there is one mobile object to be controlled is illustrated as an example, but the present invention is not limited to this, and can also be applied to a case where a plurality of mobile objects are controlled.

[0016] Fig. 2 is a diagram showing how an autonomous moving body operates in a mine, which is a site. In Fig. 2, it is assumed that an autonomous moving body B100 and a non-autonomous moving body B102 coexist and each of them moves on a travel-permitted passage B101.

[0017] The autonomous moving body B100 is, for example, a dump truck capable of carrying loads such as earth and sand or ore. The autonomous moving body B100 is not limited to a so-called four-wheel vehicle such as a dump truck, and can be any of a variety of autonomous moving bodies such as a differential two-wheel robot, an omni-wheel robot, a forklift, a towing vehicle, etc. The non-autonomous moving body B102 is, for example, a hydraulic excavator equipped with a loading function.

[0018] An example of work performed in a mine is when the autonomous moving body B100 moves to a designated position so that the non-autonomous moving body B102 can load a load, and then the loaded load is released in a designated area.

[0019] The target position to which the autonomous moving body B100 should move is managed by a management server B104. The management server B104 may be installed in the mine or in another location outside the mine. The target position determined by the management server B104 is distributed to the autonomous moving body B100 via a wireless communication line B103 in the mine.

[0020] Fig. 3 is a diagram showing a coordinate system set in a mine, and Fig. 4 is a functional block diagram showing a schematic configuration of an autonomous mobile body.

[0021] As shown in Fig. 3, an XY coordinate system is set for the autonomous mobile body B100 in the mine, the position of the autonomous mobile body B100 is represented by X-axis and Y-axis values ​​(x, y), and the direction (for example, the forward direction of the autonomous mobile body B100) is represented by the angle (θ) with the X-axis. The autonomous mobile body B100 is equipped with various sensors such as an encoder that detects the number of rotations of the wheels (not shown), an inertial sensor (IMU: Inertial Measurement Unit) that acquires the rotation speed and acceleration of the vehicle body, a LiDAR (Light Detection And Ranging), and a GNSS (Global Navigation Satellite System).

[0022] In FIG. 4, the autonomous moving object B100 is made up of a recording unit M01, a communication unit M02, a sensor M03, a moving object control unit M04, a self-position calculation unit M05, and an actuator M06.

[0023] The recording unit M01 is a recording device of the computing unit included in the autonomous moving body B100, and corresponds to an HDD (hard disk drive), an SSD (solid state drive), or a memory. Various control programs, parameters used in the control programs, and control targets distributed from the management server are recorded in the recording unit.

[0024] The communication unit M02 is a wireless communication device compatible with 5G, LTE (Long Term Evolution), etc., and can communicate with the management server B104 via a wireless communication line B103 within the mine.

[0025] The sensor M03 corresponds to a sensor provided on the autonomous moving body B100, such as the above-mentioned encoder, IMU, LiDAR, and GNSS.

[0026] The moving body control unit M04 has a function for performing calculations related to the traveling control of the moving body, and is executed by a controller (not shown) provided in the autonomous moving body B100. The calculation contents of the moving body control unit M04 will be described in detail later.

[0027] The self-position calculation unit M05 is a function that calculates its own position (x, y coordinates on a two-dimensional plane) and orientation by combining multiple sensors equipped on the autonomous moving body B100. The function of the self-position calculation unit M05 is executed in the controller, similar to the moving body control unit M04. The self-position calculation unit M05 can be realized by a technology known as SLAM (Simultaneous Localization And Mapping), so a detailed description will be omitted.

[0028] The actuator M06 corresponds to the traveling motor, steering mechanism, and braking device of the autonomous moving body B100.

[0029] The autonomous moving body B100 receives control targets and control parameters from the management server B104 via the communication unit M02, records them in the recording unit M01, and controls its own operation according to this data. If the communication cycle is sufficiently fast, the data may be used directly in the moving body control unit M04 without being stored in the recording unit M01 (shown by the dotted line in FIG. 4).

[0030] Here, the mobile object control system will be described in detail.

[0031] The mobile object control system is a system that manages the operation of the autonomous mobile object B100 within the mine based on information acquired by the autonomous mobile object B100, and most of the processing is executed by the management server B104.

[0032] As described above, the mobile object control system is made up of a mobile object position acquisition unit A101, a destination setting unit A102, a control information storage unit A103, a parameter setting unit A104, a control information storage unit A105, and a mobile object control unit A106.

[0033] The mobile object position acquisition unit A101 includes a sensor A101a and a self-position calculation unit A101b. Each function of the mobile object position acquisition unit A101 corresponds to the sensor M03 and the self-position calculation unit M05 shown in FIG.

[0034] The control information memory unit A103 holds map information, which is a database of terrain such as the curvature, gradient, and road width of the travel-permitted passage B101, vehicle body information, which is a database of vehicle specifications such as the maximum speed, maximum acceleration, and minimum turning radius of the autonomous moving body B100, and block information, which is a database of blocks composed of terrain and control targets and the control parameters corresponding to those blocks.

[0035] The destination setting unit A102 calculates a target position of the autonomous moving body B100 based on the current position of the autonomous moving body B100 calculated by the moving body position acquisition unit A101 and the work being performed within the mine, sets a movement route on the travel-permitted passage B101 from the current position to the target position, and generates a control target.

[0036] For example, the tasks to be assigned are loading, dumping, maintenance, etc., and the corresponding target positions are loading areas, dumping areas, parking areas, etc. The assignment of tasks within the mine is realized, for example, by linking with an FMS (Fleet Management System) (not shown). Note that a detailed description of the processing contents of the FMS will be omitted.

[0037] FIG. 5 is a diagram showing an example of a travel route set in a travel-permitted passage.

[0038] As shown in Fig. 5, when setting a travel route, a travel route from the current position to the target position is searched for on the travel-permitted passage B101. Methods such as the Dijkstra algorithm and the A* algorithm have been proposed for route search, and it is possible to realize the route search using these. Note that detailed explanations of the Dijkstra algorithm and the A* algorithm are omitted here.

[0039] Fig. 6 is a diagram showing how trajectory targets are set for a set movement route, and Fig. 7 is a diagram showing how speed targets are set for a set movement route.

[0040] As shown in Fig. 6 and Fig. 7, the generation of control targets generates trajectory targets and speed targets to be followed by the autonomous moving body B100. Methods such as the Timed Elastic Band Algorithm (TEB algorithm) and Model Predictive Trajectory Optimization have been proposed as generation methods that can be optimized for different control objectives (efficiency-oriented, energy-saving-oriented, safety-oriented, etc.) based on the terrain and vehicle specifications, and these can be realized. Note that detailed explanations of these methods will be omitted.

[0041] The parameter setting unit A104 includes a block search unit A104a and a parameter generation unit A104b.

[0042] Fig. 8 is a diagram showing how the set movement route and trajectory targets are divided, and Fig. 9 is a diagram showing the state of speed targets in each divided block.

[0043] 8, the block search unit A104a divides the travel route and the control target to generate blocks, searches the obtained blocks from the block information, and obtains the corresponding control parameters. The parameter generation unit A104b generates control parameters suitable for the control target based on the block topography, vehicle specifications, and the control target.

[0044] The blocks may be divided, for example, at points where the change in terrain, such as gradient or road width, relative to the distance traveled becomes constant, making it easier to search for blocks with a common tendency in terrain change, or at points where the change in trajectory target or speed target relative to the distance traveled becomes constant, making it easier to search for blocks with a common tendency in control targets. In sections where the change in trajectory target or speed target is constant, the state of the autonomous moving body B100 becomes steady, making it easier to switch control parameters between blocks.

[0045] Fig. 10 is a diagram showing an example of block information for each divided block, and Fig. 11 is a diagram showing an example of the relationship between block features and control parameters.

[0046] As shown in Fig. 10, the block information stored in the control information storage unit A103 records the route shape (topography), start target, speed target, etc. as characteristics of each divided block. The route shape (topography) stored in the control information storage unit A103 is represented, for example, by the road distance, road width at the initial position, road width change rate, curvature at the initial position, curvature change rate, gradient at the initial position, and gradient change rate. The trajectory target is represented, for example, by the initial state and state change rate. Also, the speed target is represented, for example, by the initial speed and speed change rate.

[0047] As shown in Fig. 11, the control parameters are associated based on the features shown in Fig. 10. Note that, for the sake of simplicity, Fig. 11 illustrates an example in which two features of a block are associated with the control parameters, but the present invention is not limited to this, and for example, more than two types of features may be associated with the control parameters.

[0048] In searching for blocks, if the characteristics of a newly obtained new block fall within the range that a certain control parameter P1 corresponds to (as in the case of new block A in FIG. 11), control parameter P1 is associated with new block A. On the other hand, if the characteristics of the new block do not fall within the range that any control parameter corresponds to (as in the case of new block B in FIG. 11), the existing block with the closest characteristics (smallest absolute difference in numerical values) may be associated with the corresponding control parameter, or a corresponding control parameter may be generated as described below.

[0049] The range of the control parameters may be the range of variation of the block features within which the tracking accuracy of the block to the control target is within an acceptable range when the same control parameters are used, or when control parameters for each block are generated, the range of variation of the control parameters within which the tracking accuracy of the block to the control target is within an acceptable range may be obtained, blocks with overlapping ranges are collected, and the range corresponding to the control parameters averaged over the overlapping ranges may be set from a range based on a confidence interval by calculating a normal distribution for each collected block feature. Here, the range of the tracking accuracy of the block to the control target indicates the accuracy with which the autonomous mobile body B100 can complete the assigned task, such as the accuracy with which the autonomous mobile body B100 can travel without deviating from the travel-permitted passage B101 or the accuracy with which the autonomous mobile body B100 can achieve the scheduled arrival time.

[0050] Since the block information stores the range of the control parameters and the characteristics of the corresponding blocks, it is possible to divide the movement route and the control target using this correspondence. First, the terrain, trajectory target, and speed target at the current position are set as initial values ​​to search for candidates for the corresponding control parameters. Next, the changes in the terrain, trajectory target, and speed target when moving in the direction of the path are tracked, and the block is divided into one block up to the point where there is only one candidate for the control parameter. The same process is repeated with the terrain, trajectory target, and speed target at the divided point as initial values, and the block is divided. If no corresponding control parameter is found in the search using the initial values, the block is moved in the direction of the path until the corresponding control parameter appears, and the block is divided into one block up to the point where it is found. Since no control parameters are assigned to this block, the existing block with the closest characteristics (smallest absolute difference in numerical value) may be associated with the corresponding control parameters, or the corresponding control parameters may be generated as described below. According to this method, it is possible to minimize the number of divisions when assigning control parameters, and it is also possible to minimize the number of blocks for which control parameters need to be generated.

[0051] By the above method, it becomes possible to assign control parameters to the entire movement route. Here, if the control parameters are different between blocks, there is a possibility that the control input becomes discontinuous due to switching. For example, when PID control is used, when the state quantity accumulated by the integral component parameter of the previous block is multiplied by the integral component parameter of the new block, the control input becomes discontinuous, and the tracking accuracy decreases until the state quantity is accumulated again. Therefore, in order to change the control input continuously, a buffer section that linearly connects the control parameters before and after the boundary between the blocks is provided. The length of the buffer section is set to a range in which the decrease in tracking accuracy in the buffer section does not fall below the accuracy at which the autonomous mobile body B100 can complete the assigned task.

[0052] The control parameters may be generated using, for example, Bayesian Optimization (BO). BO is an algorithm that efficiently searches for parameters based on a specific evaluation index c by repeating simulations and experiments so as to maximize or minimize the evaluation index. The evaluation index c in this embodiment indicates the degree of achievement of a control objective (such as tracking accuracy for a control target) that should be achieved within a block in order for the autonomous mobile body B100 to complete an assigned task, and may be, for example, the time tend required for the autonomous mobile body B100 to reach a target position r.

[0053] Here, we will explain the control parameter adjustment method using BO, taking as an example the task of minimizing the time tend to reach the target position r. Let the variable that summarizes the control parameters to be adjusted be the vector ρ. Since the evaluation index c is the time tend to reach the target position r, an optimization problem can be given as the problem of finding the optimal ρ* that minimizes this value. In general, this optimization problem cannot be solved directly. In BO, several solution candidates ρi are given, and the values ​​of the evaluation index c that are actually obtained are confirmed, while the function shape of the evaluation index c is estimated and the next solution candidate ρi is calculated.

[0054] FIG. 12 is a diagram showing a schematic diagram of a method for searching for solution candidates.

[0055] In Fig. 12, the black dots are the evaluation values ​​obtained from the solution candidates ρi (i = 1, ..., 6) so far. By using the solution candidates obtained so far, it is possible to calculate the estimated value of the function shape (solid line) and its variance (dashed line). The variance is large in areas where there are no solution candidates ρi so far. The next solution candidate ρ7 (see "△" in Fig. 12) is determined taking into account the estimated value of the function shape and the variance. By performing the above processing, it is possible to search for control parameters very efficiently compared to the case of exhaustively verifying the solution candidates ρi.

[0056] Here, even in different blocks, if the evaluation index c calculated with the same control parameter is equivalent, that is, if the control objective can be achieved equally in each block, the block and the control parameter may be stored in the block information in correspondence with each other. In this case, there may be multiple ranges that a certain control parameter corresponds to, as in the case of control parameter P1 in FIG. 11.

[0057] The control information storage unit A105 acquires the blocks on the movement route and the control parameters corresponding to them from the parameter setting unit A104 and stores them.

[0058] The mobile unit control unit A106 calculates a control input to the actuator M06 that causes the position and orientation of the autonomous mobile unit B100 acquired by the self-position calculation unit A101b to follow a control target. The control parameters used to calculate the control input are acquired from the control information storage unit A105, and are control parameters corresponding to the block corresponding to the current position acquired by the self-position calculation unit A101b. As a control method for calculating the control input, methods such as PID control and model predictive control (MPC) have been proposed, and can be realized by these. Note that detailed explanations of these methods will be omitted.

[0059] When the moving route is long or when the blocks are divided into small pieces, the blocks and the corresponding control parameters stored in the control information storage unit A105 become huge, so it is expected that the recording capacity of the recording device (recording unit M01) mounted on the autonomous moving body B100 will be insufficient. Therefore, it is desirable that the blocks on the moving route and the corresponding control parameters are managed by the recording device of the management server B104. In such an implementation form, based on the position of the autonomous moving body B100 acquired by the self-position calculation unit A101b, the blocks and control parameters that are expected to be requested from the moving body control unit A106 are delivered from the management server B104 to the autonomous moving body B100, and the autonomous moving body B100 travels while receiving the necessary information.

[0060] FIG. 13 is a flowchart showing the process of the mobile object control system.

[0061] 13, the moving body control system first checks the current position of the autonomous moving body B100 (step S100). This process is realized by the function of the moving body position acquisition unit A101.

[0062] Next, based on the acquired position of the autonomous moving body B100, it is determined whether there is a task that can be assigned to the autonomous moving body B100 (step S110). If the determination result in step S110 is NO, that is, if it is determined that there is no task that can be assigned to the autonomous moving body B100, the autonomous moving body B100 has no load to be released or loaded, and there is no need to move the autonomous moving body B100, so the process returns to step S100.

[0063] If the determination result in step S100 is YES, that is, if it is determined that there is a task that can be assigned to the autonomous moving body B100, then a target position r corresponding to the assigned task is determined (step S120).

[0064] In addition, even if the autonomous moving body B100 has no cargo to be dumped or loaded, that is, even if the determination result in step S110 is NO, if the autonomous moving body B100 would hinder the movement of other moving bodies by staying there, a task to move it to another location may be generated. Similarly, if the autonomous moving body B100 is a battery-powered vehicle, if the remaining battery level is low, a task to move it to a charging station may be generated, and if the autonomous moving body B100 is a gasoline-powered vehicle, if the remaining gasoline level is low, a task to move it to a refueling station may be generated.

[0065] After the process of step S120 is completed, a movement route of the autonomous moving body B100 is set (step S130), and a control target is generated (step S140). The processes of steps S110, S120, S130, and S140 are realized by the function of the destination setting unit A102 using the information stored in the control information storage unit A103.

[0066] After the process of step S140 is completed, the moving route and the control target are divided into blocks (step S150), and the blocks on the moving route are searched for using block information to determine whether or not corresponding control parameters can be obtained from the block information for all blocks on the moving route (step S160). Note that the processes of steps S150 and S160 are realized by the function of the block search unit A104a using information stored in the control information storage unit A103.

[0067] If the determination result in step S160 is NO, that is, if there is a block among the searched blocks whose corresponding control parameters do not exist in the block information, then control parameters are generated for the blocks whose corresponding control parameters do not exist in the block information (step S161). This process is realized by the function of the parameter generation unit A104b using the information stored in the control information storage unit A103.

[0068] If the determination result in step S160 is YES, or if the processing of step S161 is completed, the control parameters of the block corresponding to the current position X of the autonomous moving body B100 are then set (step S170). This processing is realized by the function of the control information storage unit A105. Note that, if all blocks and control parameters are recorded in the management server B104, necessary information is provided to the autonomous moving body B100 at the timing of the processing of step S170.

[0069] Next, the control input to the actuator M06 is calculated using the control parameters set in step S170 (step S180), and the process ends. Note that the process of step S180 is realized by the function of the moving object control unit A106.

[0070] The above-mentioned processing of steps S100 to S180 is repeated for each control cycle. By performing the processing for each control cycle, even if the current position deviates from the control target, a control target is generated based on the current position, so that an appropriate control target is given. Also, if the current position does not deviate from the control target, it is sufficient to perform the processing of steps S179 and S180 for each control cycle, and the calculation cost can be reduced.

[0071] In the present embodiment configured as described above, the burden of introducing an autonomous mobile body to a site can be reduced, and the mobile body can be introduced quickly. In other words, if a system designer prepares a database of blocks and their corresponding control parameters in advance, the operator does not need to perform control design suitable for the control target, and can optimally control the mobile body for each task. In particular, when a block generated in the past can be reused (when it can be expressed by rearranging existing blocks or when the same task is assigned to the same position as in the past), the process of generating control parameters is not required, and the same execution result can be obtained while reducing calculation costs.

[0072] <Second embodiment> A second embodiment of the present invention will be described with reference to FIG.

[0073] This embodiment is a mobile object control system that can handle changes in vehicle performance and disturbances that are difficult to record in advance in block information. In this embodiment, the same reference numerals are used for the same parts as in the first embodiment, and the description will be omitted as appropriate.

[0074] In a mine, a situation may occur where obstacles such as rocks spilled during transportation fall onto the travel permission passage B101. In addition, since the mass of an autonomous vehicle used in a mine is large, a braking device using a friction brake used in an emergency heats up after one use, and the braking performance decreases until it cools down, so there is a restriction that it cannot be used continuously. Such obstacles and changes in vehicle performance occur exceptionally, making it difficult to record them as block information. Therefore, in this embodiment, model predictive control (MPC) is introduced into the mobile unit control unit A106 of the mobile unit control system in the first embodiment, so that even if there is a disturbance or performance change such as an obstacle not recorded in the block information or a decrease in the braking performance of the vehicle, a control input that can follow the control target can be generated, and the assigned work in the mine can be more reliably accomplished.

[0075] FIG. 1 is a functional block diagram showing a schematic overall configuration of a mobile object control system according to the present embodiment.

[0076] In FIG. 1, the mobile object control system mainly includes a mobile object position acquisition unit A101, a destination setting unit A102, a control information storage unit A103, a parameter setting unit A104, a control information storage unit A105, and a mobile object control unit A106.

[0077] The moving object control unit A106 has an evaluation function setting unit A106a and a prediction control unit A106b.

[0078] The evaluation function setting unit A106a constructs an evaluation function by combining several evaluation functions and parameters related to the evaluation functions. For example, as shown in the following (Equation 1) to (Equation 3), a vector rk is defined that summarizes the target position (xrk, yrk) and target orientation θrk of the autonomous moving body B100 at each time, and an evaluation function J can be constructed using a function (the first term in the following (Equation 1)) that evaluates the deviation ek=Xk-rk between the current state (xk, yk, θk) of the autonomous moving body B100 and the target state, and a function (the second term in the following (Equation 1)) that evaluates the magnitude of the control input uk.

[0079]

number

[0080]

number

[0081]

number

[0082] The symbol T in the above (Equation 1) is a symbol representing transposition. Furthermore, the matrix Q is a weighting parameter relating to the deviation ek, the matrix R is a weighting parameter relating to the input uk, and the variable N is a parameter representing the evaluation interval (prediction interval). In this way, the evaluation function setting unit A106a includes a plurality of parameters, and these parameters are recorded in the control information storage unit A105.

[0083] Note that the above (Equation 1) shows one example of the evaluation function J, and is not limited to this. For example, an evaluation function in which only the final step N is a separate evaluation (terminal cost) may be used, as shown in the following (Equation 4).

[0084]

number

[0085] The predictive control unit A106b calculates a control input uk in accordance with the concept of MPC so as to reduce the value of the evaluation function J set by the evaluation function setting unit A106a.

[0086] In MPC, in order to evaluate the evaluation function J up to the interval of the evaluation function (behavior from the current time to the Nth step ahead), it is necessary to predict the future behavior of the autonomous mobile body B100. The behavior prediction of the mobile body up to the Nth step ahead can be calculated recursively by inputting the control input u obtained to minimize the above (Equation 1) (or (Equation 4)) into the equation of motion of the autonomous mobile body B100.

[0087] MPC has the advantage of being able to explicitly handle constraint conditions. For example, in the case of the autonomous vehicle shown in Fig. 3, the upper and lower limits of the driving speed v are determined by the rotational speed limit of the driving motor and the braking limit of the braking device. By incorporating the operating characteristics of such actuators as constraint conditions, it becomes possible to generate control inputs that the autonomous vehicle can actually execute. An MPC that takes such constraint conditions into account can be expressed as shown in the following (Equation 5) and (Equation 6).

[0088]

number

[0089]

number

[0090] In the above formula (6), the symbol [st] is an abbreviation of [subject to], and means that the optimization problem is solved under the conditions following [st]. The subscripts max and min correspond to the upper and lower limits, respectively. In general, to facilitate design, the weight parameter matrices Q and R are given as diagonal matrices. For example, Q can be expressed using the weight Qx of the x-coordinate, the weight Qy of the y-coordinate, and the weight Qθ of the orientation.

[0091] The control information storage unit A105 stores blocks on a movement route and weighting matrices Qi,Ri (i is an index given to a block) as corresponding control parameters.

[0092] In the moving object control unit A106, the evaluation function setting unit A106a acquires control parameters from the control information storage unit A105 based on the block including the predicted position calculated by the prediction control unit A106b, and sets an evaluation function.

[0093] As described above, by introducing MPC and reflecting it in the constraint conditions, it becomes possible to respond to disturbances and performance changes. However, in an environment where there is an obstacle on the trajectory target, the situation may deviate from the situation assumed in the block so that the trajectory target cannot be achieved, and in this case, the control parameters may become inappropriate. As a countermeasure, there are two methods: one is to regenerate the control target for the entire movement route based on the current position and reset the control parameters, and the other is to set a buffer section from the current position to the position where the expected situation will be restored. In particular, the latter method has the advantage of reducing calculation costs because it does not require recalculation for the entire movement route.

[0094] Here, a method for setting the buffer zone will be described. Since the MPC can predict the state quantity occurring ahead and calculate the control input, the control input can be adjusted so as to improve the tracking accuracy ahead after returning to the expected situation rather than the tracking accuracy around the current position that deviates from the expected situation. For this purpose, the control parameters in the buffer zone may be set to general-purpose control parameters that emphasize stabilizing the running, or may be set to reduce the weighting parameters by a predetermined ratio to reduce the influence of the buffer zone in the entire prediction zone. The length of the buffer zone may be set from the current position to a position in the prediction zone where the tracking error with the control target falls below a predetermined ratio, or may be set from the current position to the start position of the next block.

[0095] The other configurations are similar to those of the first embodiment.

[0096] The present embodiment configured as above can also provide the same effects as the first embodiment.

[0097] Furthermore, by introducing MPC into the mobile unit control unit A106, it is possible to generate control inputs that can track the control targets even in the presence of exceptional disturbances or performance changes, such as obstacles or reduced vehicle braking performance that are not recorded in the block information, making it possible to more reliably accomplish the tasks assigned to the autonomous mobile unit B100 within the mine.

[0098] <Additional Notes> The present invention is not limited to the above-described embodiments, and includes various modified examples and combinations of the embodiments within the scope of the gist of the present invention. The present invention is not limited to those having all the configurations described in the above-described embodiments, and includes those in which some of the configurations are changed or deleted. The above-described configurations, functions, etc. may be realized in part or in whole by designing them as an integrated circuit, for example. The above-described configurations, functions, etc. may be realized in software by a processor interpreting and executing a program that realizes each function. [Explanation of symbols]

[0099] A101...mobile body position acquisition unit, A101a...sensor, A101b...self-position calculation unit, A102...destination setting unit, A103...control information storage unit, A104...parameter setting unit, A104a...block search unit, A104b...parameter generation unit, A105...control information storage unit, A106...mobile body control unit, A106a...evaluation function setting unit, A106b...prediction control unit, B100...autonomous mobile body, B101...travel-permitted passage, B102...non-autonomous mobile body, B103...wireless communication line, B104...management server, M01...recording unit, M02...communication unit, M03...sensor, M04...mobile body control unit, M04...direct mobile body control unit, M05...self-position calculation unit, M06...actuator

Claims

1. a destination setting unit that determines a destination for the moving body and generates a moving route including a path shape and a control target to the destination; a parameter setting unit that sets control parameters to be used on the movement route set by the movement destination setting unit; an information storage unit that stores a travel record that records at least a route shape, a control target, and a control parameter combination along which the moving body has autonomously traveled in the past; In a mobile object control system comprising: The parameter setting unit is A past block is generated by dividing the route shape and the control target of the driving record, A set of past blocks is generated that is formed by similar past blocks to which the same control parameters can be assigned; A current block is generated by dividing the path shape of the movement route and the control target; Compare the path shape and control target of the current block with the path shape and control target of the past block set; A mobile object control system that generates control parameters corresponding to a set of past blocks similar to a current block.

2. 2. The mobile object control system according to claim 1, The mobile object control system is characterized in that the parameter setting unit generates blocks divided at points where a rate of change of the route shape with respect to the distance traveled becomes constant.

3. 2. The mobile object control system according to claim 1, A mobile object control system, wherein the parameter setting unit generates blocks divided at points where a rate of change of the control target with respect to the travel distance becomes constant.

4. 2. The mobile object control system according to claim 1, The mobile object control system is characterized in that the parameter setting unit generates blocks divided at points where the blocks become included in a single past block set.

5. 2. The mobile object control system according to claim 1, The parameter setting unit provides a buffer section before and after a boundary of each current block, and generates control parameters that smoothly connect the control parameters generated for the previous and next current blocks in the buffer section.

6. 2. The mobile object control system according to claim 1, A mobile object control system characterized in that the parameter setting unit calculates an evaluation index indicating the degree of achievement of a control goal, and generates a past block set that collects past blocks that have the same evaluation index with the same control parameters.

7. 2. The mobile object control system according to claim 1, a self-position calculation unit that calculates a self-position of the moving body based on a detection result of a sensor that detects a state quantity of an actuator provided in the moving body; a moving object control unit that controls a behavior of the moving object along the moving route set by the moving destination setting unit, The moving object control unit includes: an evaluation function setting unit that constructs an evaluation function defined by one or more functions expressed using state quantities of the moving object and command values ​​to the actuators and weight parameters corresponding to those functions; a prediction control unit that has a function of predicting a behavior of a moving object up to a prediction step number, and calculates a control input in each prediction step so that a value of the evaluation function determined by the evaluation function setting unit is reduced from a value in a previous step; A mobile object control system characterized in that the parameter setting unit is a weight parameter used in the evaluation function setting unit, and the parameter setting unit provides the weight parameter to the evaluation function setting unit based on the current position of the mobile object calculated by the self-position calculation unit and the predicted position of the mobile object calculated by the prediction control unit.

8. 8. The mobile object control system according to claim 7, The parameter setting unit provides a buffer zone ahead of the current position of the moving body calculated by the self-position calculation unit, and sets a weighting parameter for the buffer zone that prioritizes tracking accuracy from the end of the buffer zone to the end of the predicted position of the moving body calculated by the prediction control unit over tracking accuracy in the buffer zone.

9. A step of determining a destination for a moving body and generating a moving route including a path shape and a control target to the destination; and a step of setting control parameters to be used on the set movement route, The step of setting the control parameters includes: A step of generating past blocks by dividing a route shape and a control target of a travel record that records at least a combination of a route shape, a control target, and a control parameter along which the moving body has autonomously traveled in the past; A procedure for generating a past block set formed by similar past blocks to which the same control parameters can be assigned; A step of generating a current block by dividing the path shape of the movement route and the control target; a step of comparing the path shape and control target of the current block with the path shape and control target of the past block set, and generating control parameters corresponding to the past block set similar to the current block; A moving object control method comprising:

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