WO2025022770A1 - Moving body control system and moving body control method - Google Patents

Abstract

The present invention comprises: a movement destination setting unit that generates a movement route including a route shape and a control target; a parameter setting unit that sets a control parameter to be used in the movement route; and an information storage unit that stores a travel record in which a route shape along which a moving body has autonomously traveled in the past, the control target, and the control parameter are combined. A past block in which the route shape and the control target in the travel record are divided is generated, a past block set formed by similar past blocks in which the same control parameter is associated is generated, a current block obtained by dividing the route shape of the movement route and the control target is generated, the route shape and the control target of the current block and the past block set are compared, and a control parameter corresponding to a past block set that is similar to the current block is generated. This makes it possible to reduce the burden at the time of new introduction of the autonomous moving body into a site, and to quickly introduce the autonomous moving body into the site.

Description

MOBILE BODY CONTROL SYSTEM AND MOBILE BODY CONTROL METHOD

The present invention relates to a mobile object control system and a mobile object control method.

To solve the driver shortage in transporting soil at construction sites and mines, and in shuttles 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 given to the autonomous vehicles (trajectory targets and target speed distributions expressed by nodes and branches/edges, etc.) differ, so it becomes necessary to design control targets every time the task changes, which imposes a large 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 target changes, 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.

A conventional technique for addressing such issues is known, for example, from Patent Document 1. Patent Document 1 discloses a vehicle driving support device that outputs a target driving pattern that serves as a reference for controlling the vehicle speed according to the vehicle's driving state, and that, each time the vehicle travels through a section previously set on a map, classifies the vehicle's driving state, including the presence or absence of a preceding vehicle and the presence or absence of a following vehicle, and stores a driving pattern that indicates the 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 that is classified as the same vehicle driving state as the current vehicle driving state from among the stored driving patterns.

JP 2013-193671 A

In the above conventional technology, a target driving pattern, which is the control target, is generated from driving patterns recorded during tasks performed by an autonomous vehicle in the past, so this is effective in reducing the burden of repeated operations at the same site or with the same vehicle (autonomous vehicle).

However, when an autonomous vehicle is newly introduced to a site, conditions are likely to be unique depending on the combination of the site conditions, the vehicle being used, the tasks given, etc., so it is difficult to obtain driving patterns for the same conditions as the site where the autonomous vehicle is being introduced from past records at other sites. In other words, when an autonomous vehicle is newly introduced, it is necessary to set new control targets, etc., so burden reduction is limited and it is thought that introduction to the site will take time.

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 new autonomous mobile objects to a site and can quickly introduce them to the site.

The present application includes multiple means for solving the above problem, but one example is a mobile body control system that includes a destination setting unit that determines a destination for a mobile body and generates a movement route including a path 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 path shape, a control target, and a control parameter along which the mobile body has autonomously traveled in the past, in which the parameter setting unit generates past blocks by dividing the path 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 path shape and control target of the movement route, compares the path shape and control target of the current block with the path shape and control target of the past block set, and generates control parameters corresponding to the past block set similar to the current block.

The present invention can reduce the burden of introducing an autonomous mobile device to a site, and can quickly introduce the device to the site.

1 is a functional block diagram illustrating a schematic overall configuration of a mobile object control system according to a first embodiment. FIG. 1 is a diagram showing an autonomous moving body operating in a mine, which is a site of the autonomous moving body; FIG. 1 is a diagram showing a coordinate system set in a mine. FIG. 2 is a functional block diagram illustrating a configuration of an autonomous moving body. FIG. 11 is a diagram showing an example of a travel route set in a travel-permitted passage; FIG. 13 is a diagram showing how trajectory targets are set on a set movement route. FIG. 13 is a diagram showing how a speed target is set for a set movement route. FIG. 13 is a diagram showing a state in which a set movement route and a trajectory target are divided. FIG. 13 is a diagram showing the state of a velocity target in each divided block. FIG. 11 is a diagram showing an example of block information for each divided block. FIG. 11 is a diagram illustrating an example of a relationship between block features and control parameters. FIG. 10 is a diagram illustrating a method for searching for solution candidates. 4 is a flowchart showing the processing contents of the mobile object control system. FIG. 11 is a functional block diagram illustrating an overall configuration of a mobile object control system according to a second embodiment.

The following describes an embodiment of the present invention with reference to the drawings.

The mobile object control system in this embodiment controls mobile objects such as robots and vehicles capable of autonomous operation, 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 is 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 generating movement paths for mobile objects operating in mines, but can also be applied, for example, to generating movement paths for transport vehicles in ports and paths for robots moving in theme parks.

First Embodiment
A first embodiment of the present invention will be described with reference to FIGS.

FIG. 1 is a functional block diagram that shows a schematic diagram of the overall configuration of a mobile object control system according to this embodiment.

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 simplicity of explanation, an example is shown in which there is one mobile object to be controlled, but this is not limited to this, and the present invention can also be applied to cases in which multiple mobile objects are controlled.

FIG. 2 is a diagram showing autonomous mobile bodies operating in a mine, which is a site. In FIG. 2, it is assumed that autonomous mobile bodies B100 and non-autonomous mobile bodies B102 are mixed and each of them moves along a travel-permitted path B101.

The autonomous mobile body B100 is, for example, a dump truck capable of carrying loads such as soil or ore. The autonomous mobile body B100 is not limited to so-called four-wheel vehicles such as dump trucks, and can handle various types of autonomous mobile bodies such as differential two-wheel robots, omni-wheel robots, forklifts, and towing vehicles. The non-autonomous mobile body B102 is, for example, a hydraulic excavator equipped with a loading function.

Examples of work performed in a mine include an autonomous mobile body B100 moving to a specified position so that a non-autonomous mobile body B102 can load a load, and then discharging the loaded load in a specified area.

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

Fig. 3 shows a coordinate system set in the mine. Fig. 4 is a functional block diagram showing the configuration of an autonomous mobile unit.

As shown in Figure 3, an XY coordinate system is set up in the mine for the autonomous mobile body B100, with the position of the autonomous mobile body B100 represented by X-axis and Y-axis values (x, y), and the orientation (e.g., the forward direction of the autonomous mobile body B100) indicated 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 rotation speed of the wheels (not shown), an inertial sensor (IMU: Inertial Measurement Unit) that acquires the rotational speed and acceleration of the vehicle body, LiDAR (Light Detection And Ranging), and GNSS (Global Navigation Satellite System).

In FIG. 4, the autonomous mobile object B100 is composed of a recording unit M01, a communication unit M02, a sensor M03, a mobile object control unit M04, a self-position calculation unit M05, and an actuator M06.

The recording unit M01 is a recording device for the computing unit provided in the autonomous mobile unit B100, and corresponds to an HDD (hard disk drive), SSD (solid state drive) or memory. The recording unit records various control programs, parameters used in the control programs, and control targets distributed from the management server.

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.

Sensor M03 corresponds to sensors installed on the autonomous mobile unit B100, such as the encoder, IMU, LiDAR, and GNSS described above.

The mobile unit control unit M04 is a function that performs calculations related to the travel control of the mobile unit, and is executed in a controller (not shown) that is installed in the autonomous mobile unit B100. The calculations performed by the mobile unit control unit M04 will be described in detail later.

The self-position calculation unit M05 is a function that calculates the autonomous mobile unit B100's own position (x, y coordinates on a two-dimensional plane) and orientation by combining multiple sensors attached to the autonomous mobile unit B100. The functions of the self-position calculation unit M05 are executed in the controller, similar to the mobile unit 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 explanation will be omitted.

Actuator M06 corresponds to the driving motor, steering mechanism, and braking device of the autonomous mobile body B100.

The autonomous mobile 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. Note that if the communication cycle is sufficiently fast, the data may not be stored in the recording unit M01 but may be used directly by the mobile body control unit M04 (shown by the dotted line in Figure 4).

Here, we'll explain the mobile control system in detail.

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

As described above, the mobile object control system is 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.

The mobile object position acquisition unit A101 is composed of 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. 4.

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

The destination setting unit A102 calculates the 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 carried out within the mine, sets a movement route on the travel permission passage B101 from the current position to the target position, and generates a control target.

For example, the tasks that can be assigned are loading, dumping, maintenance, etc., and the corresponding target locations are loading areas, dumping areas, parking areas, etc. The allocation of tasks within the mine is achieved, for example, by linking with an FMS (Fleet Management System) not shown in the figure. Note that a detailed explanation of the processing content of the FMS is omitted here.

Figure 5 shows an example of a travel route set in a travel-permitted passage.

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 this can be realized by using these. Note that a detailed explanation of the Dijkstra algorithm and the A* algorithm will be omitted.

FIG. 6 shows how trajectory targets are set for a set movement route. Also, FIG. 7 shows how speed targets are set for a set movement route.

As shown in Figures 6 and 7, control target generation involves generating trajectory targets and speed targets to be followed by the autonomous mobile 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, safety-oriented, etc.) based on the terrain and vehicle specifications, and these can be used to achieve this. Note that a detailed explanation of these methods will not be given here.

The parameter setting unit A104 has a block search unit A104a and a parameter generation unit A104b.

Figure 8 shows the division of the set movement route and trajectory target. Figure 9 shows the speed target for each divided block.

As shown in FIG. 8, the block search unit A104a divides the travel route and control targets to generate blocks, searches the resulting blocks from the block information, and obtains the corresponding control parameters. The parameter generation unit A104b generates control parameters suitable for the control targets based on the block's terrain, vehicle specifications, and control targets.

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

FIG. 10 shows an example of block information for each divided block. Also, FIG. 11 shows an example of the relationship between block characteristics and control parameters.

As shown in FIG. 10, the block information stored in the control information storage unit A103 records the route shape (topography), starting target, speed target, etc. as the 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.

As shown in FIG. 11, the control parameters are associated based on the features shown in FIG. 10. Note that, for simplicity of explanation, FIG. 11 shows an example in which two features of a block are associated with the control parameters, but this is not limited thereto, and for example, more than two types of features may be associated with the control parameters.

When searching for blocks, if the characteristics of the 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.

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 are generated for each block, 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 determined, blocks with overlapping ranges may be collected, and a normal distribution may be calculated for each collected block feature to set the range corresponding to the averaged control parameter for the overlapping range from a range based on the confidence interval. Here, the acceptable range of 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 path B101 or the accuracy with which the autonomous mobile body B100 can achieve the scheduled arrival time.

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 using 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 a corresponding control parameter may be generated as described below. This method makes it possible to minimize the number of divisions when assigning control parameters, and also minimizes the number of blocks for which control parameters need to be generated.

The above method makes it possible to assign control parameters to the entire movement route. Here, if the control parameters differ between blocks, there is a possibility that the control input will become discontinuous when switching. For example, if PID control is used, the control input will become discontinuous when the state quantity accumulated using the integral component parameters of the previous block is multiplied by the integral component parameters of the new block, and the tracking accuracy will decrease 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 is provided before and after the boundary between blocks. 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.

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 this evaluation index. In this embodiment, the evaluation index c 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 until the autonomous mobile body B100 reaches the target position r.

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. The variable that summarizes the control parameters to be adjusted is 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.

Figure 12 is a diagram that shows a schematic diagram of a method for searching for solution candidates.

In Figure 12, the black dots are evaluation values obtained from the solution candidates ρi (i = 1, ..., 6) obtained 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 Figure 12) is determined by 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.

Here, even in different blocks, if the evaluation index c calculated with the same control parameters is equivalent, that is, the control objective can be achieved equally within each block, the block and the control parameters may be associated and stored in the block information. In this case, there may be multiple ranges that a certain control parameter corresponds to, such as control parameter P1 in Figure 11.

The control information storage unit A105 obtains the blocks on the movement route and the corresponding control parameters from the parameter setting unit A104 and stores them.

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 obtained by the self-position calculation unit A101b to follow the control target. The control parameters used to calculate the control input are obtained from the control information storage unit A105, and correspond to the block corresponding to the current position obtained by the self-position calculation unit A101b. Proposed control methods for calculating the control input include PID control and model predictive control (MPC), and these can be used to realize the control. A detailed explanation of these methods will be omitted.

When the travel route is long or the blocks are divided into small pieces, the number of blocks and the corresponding control parameters stored in the control information storage unit A105 will be enormous, and it is expected that the recording capacity of the recording device (recording unit M01) mounted on the autonomous mobile unit B100 will be insufficient. Therefore, it is desirable that the blocks on the travel 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 mobile unit B100 acquired by the self-position calculation unit A101b, the blocks and control parameters that are expected to be requested by the mobile unit control unit A106 are delivered from the management server B104 to the autonomous mobile unit B100, and the autonomous mobile unit B100 travels while receiving the necessary information.

Figure 13 is a flowchart showing the processing performed by the mobile control system.

In FIG. 13, the mobile object control system first checks the current position of the autonomous mobile object B100 (step S100). This process is realized by the function of the mobile object position acquisition unit A101.

Next, based on the acquired position of the autonomous mobile body B100, it is determined whether there is a task that can be assigned to the autonomous mobile 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 mobile body B100, there is no load to be released or loaded on the autonomous mobile body B100, and there is no need to move the autonomous mobile body B100, so the process returns to step S100.

Also, if the determination result in step S100 is YES, i.e., if it is determined that there is a task that can be assigned to the autonomous mobile body B100, then the target position r corresponding to the assigned task is determined (step S120).

Note that even if the autonomous moving body B100 does not have any cargo to be dumped or loaded, that is, if the determination result in step S110 is NO, if the autonomous moving body B100 staying there would hinder the movement of other moving bodies, a task to move it to another location may be generated. Similarly, if the autonomous moving body B100 is a battery-powered vehicle, a task to move it to a charging station may be generated if the battery level is low, and if the autonomous moving body B100 is a gasoline-powered vehicle, a task to move it to a refueling station may be generated if the gasoline level is low.

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

After the processing of step S140 is completed, the movement route and the control target are divided into blocks (step S150), and the blocks on the movement 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 movement route (step S160). Note that the processing of steps S150 and S160 is realized by the function of the block search unit A104a using the information stored in the control information storage unit A103.

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

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 mobile 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, the necessary information is provided to the autonomous mobile body B100 at the timing of the processing of step S170.

Then, 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 mobile unit control unit A106.

The above 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, and an appropriate control target is provided. Furthermore, 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, thereby reducing calculation costs.

In this embodiment configured as described above, the burden of introducing a new autonomous mobile body to a site can be reduced, and the mobile body can be introduced quickly to the site. In other words, if the 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 objectives, and can optimally control the mobile body for each task. In particular, if blocks generated in the past can be reused (if they can be expressed by rearranging existing blocks or if the same task is assigned to the same position as in the past), the process of generating control parameters is unnecessary, and the same execution results can be obtained while reducing calculation costs.

Second Embodiment
A second embodiment of the present invention will be described with reference to FIG.

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

In mines, obstacles such as rocks that have fallen during transportation may land on the travel permission passage B101. In addition, because the autonomous vehicles used in mines have a large mass, the braking system using friction brakes used in emergencies 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 to the mobile unit control unit A106 of the mobile unit control system in the first embodiment, making it possible to generate control inputs that can follow the control target even in the presence of disturbances or performance changes such as obstacles not recorded in the block information or decreased vehicle braking performance, and to more reliably accomplish the assigned work in the mine.

FIG. 1 is a functional block diagram that shows a schematic diagram of the overall configuration of a mobile object control system according to this embodiment.

In FIG. 1, the mobile object control system is roughly 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.

The mobile unit control unit A106 has an evaluation function setting unit A106a and a prediction control unit A106b.

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), it is possible to define a vector rk that combines the target position (xrk, yrk) and target orientation θrk of the autonomous mobile body B100 at each time, and to construct an evaluation function J that uses a function (first term in (Equation 1) below) that evaluates the deviation ek = Xk-rk between the current state (xk, yk, θk) of the autonomous mobile body B100 and the target state, and a function (second term in (Equation 1) below) that evaluates the magnitude of the control input uk.

The symbol T in the above (Equation 1) is a symbol representing transposition. Furthermore, the matrix Q is a weighting parameter related to the deviation ek, the matrix R is a weighting parameter related 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 multiple parameters, and these parameters are recorded in the control information storage unit A105.

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).

The prediction control unit A106b calculates the 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.

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

MPC has the advantage of being able to explicitly handle constraint conditions. For example, in the case of the autonomous vehicle shown in Figure 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. MPC that takes such constraint conditions into account can be expressed as shown in the following (Equation 5) and (Equation 6).

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

The control information storage unit A105 stores blocks on the movement route and the weight matrices Qi, Ri (i is an index assigned to the block) as the corresponding control parameters.

In the mobile object control unit A106, the evaluation function setting unit A106a acquires control parameters from the control information storage unit A105 based on the block containing the predicted position calculated by the prediction control unit A106b, and sets the evaluation function.

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 are obstacles on the trajectory target, there are cases where the situation deviates from the situation assumed in the block and the trajectory target cannot be achieved, and in this case, the control parameters may no longer be appropriate. As a countermeasure, there is a method of regenerating the control target for the entire movement route based on the current position and resetting the control parameters, and a method of setting up a buffer section from the current position to the position where the assumed situation will be restored. In particular, the latter method has the advantage of reducing calculation costs, as it does not require recalculation for the entire movement route.

Here, a method for setting the buffer section will be explained. Since the MPC can predict state quantities occurring ahead and calculate the control input, it can adjust the control input so as to improve the tracking accuracy ahead after returning to the expected situation, rather than the tracking accuracy around the current position, which deviates from the assumption. For this reason, the control parameters in the buffer section may be set to general-purpose control parameters that focus on stabilizing driving, or the weighting parameters may be reduced by a specified percentage to reduce the influence of the buffer section on the entire prediction interval. The length of the buffer section may be set to a position in the prediction interval from the current position to the position where the tracking error with the control target falls below a specified percentage, or it may be set to from the current position to the start position of the next block.

The rest of the configuration is the same as in the first embodiment.

The present embodiment, configured as described above, can achieve the same effects as the first embodiment.

In addition, by introducing MPC into the mobile unit control unit A106, it is possible to generate control inputs that can track the control target even in the presence of disturbances or performance changes, such as exceptional obstacles or deterioration of the vehicle's 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.

<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.

　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...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 (9)

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. 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. 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. 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. 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. 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. 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. 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. 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 method for controlling a moving object, comprising the steps of: comparing a path shape and control target of a current block with a path shape and control target of a set of past blocks; and generating control parameters corresponding to a set of past blocks similar to the current block.

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