JP7791073B2 - Mobile object control system, control method thereof, mobile object, program, and recording medium - Google Patents

Description

The present invention relates to a mobile object control system, a control method therefor, a mobile object, a program, and a recording medium.

In recent years, there has been growing demand for ultra-small mobile vehicles (micromobility) to support people's mobility within small areas. Micromobility vehicles include vehicles with a passenger capacity of around one person, and vehicles that travel alongside people while carrying luggage instead of passengers. Because micromobility can travel in both areas where automobiles travel and areas where pedestrians travel, it requires not only autonomous driving technology for traveling on roads, but also autonomous movement technology for free spaces such as sidewalks. As it is expected that various obstacles will be present in the path of micromobility's travel, a highly flexible driving trajectory is required to flexibly avoid these obstacles.

Non-Patent Document 1 proposes technology for generating a driving trajectory based on a clothoid curve so that an autonomous vehicle can travel on a road with a complex shape. Non-Patent Document 2 proposes technology for generating a driving trajectory based on a multidimensional curve that passes through endpoints set on a driving lane, as a driving trajectory for avoiding obstacles in an emergency.

MARCUS LUNDBERG, “Path planning for autonomous vehicles using clothoid based smoothing of A* generated paths and optimal control” (https://www.diva-portal.org/smash/get/diva2:1150741/FULLTEXT01.pdf), 2017 Wenda Xu and 4 others, "A Real-Time Motion Planner with Trajectory Optimization for Autonomous Vehicles" (https://www.ri.cmu.edu/pub_files/2012/5/ICRA12_xuwd_Final.pdf), 2012

By the way, since micromobility vehicles are used by people, it is necessary to ensure an appropriate ride comfort even when they travel along a highly flexible driving trajectory, i.e., a trajectory with a complex shape.

The present invention was made in consideration of the above-mentioned problems, and its purpose is to realize technology that can simultaneously generate a highly flexible running trajectory while ensuring a comfortable ride.

According to the present invention,
A mobile object control system for controlling the operation of a mobile object,
a generation means for generating a trajectory along which the moving object should travel, using a trajectory from the position of the moving object to a target position, the trajectory being formed by combining a plurality of trajectories, each of which has a curvature that changes linearly , and a plurality of curvature change points, each of which has a curvature that changes nonlinearly;
a determination means for determining a control amount for controlling the traveling of the moving body based on the generated trajectory ,
The generation means substitutes the trajectory in which the curvatures of the plurality of curvature change points are changed into a cost function to calculate a cost using the cost function, and repeatedly changes the curvatures of the plurality of curvature change points using the gradient of the cost function so as to reduce the cost, thereby determining the curvatures of the plurality of curvature change points, thereby generating a trajectory on which the mobile body should travel .

This invention makes it possible to generate a highly flexible running trajectory while ensuring a comfortable ride.

FIG. 1 is a diagram illustrating an example of the configuration of a moving body according to an embodiment of the present invention. FIG. 1 is a block diagram showing an example of the configuration of a control system of a moving body according to an embodiment; FIG. 1 is a block diagram showing an example of a functional configuration related to a control unit of a moving body according to an embodiment; FIG. 1 is a diagram schematically illustrating an example of a grid map according to an embodiment. FIG. 1 is a diagram for schematically explaining a local path (trajectory) of a moving object according to an embodiment; FIG. 1 is a diagram illustrating an example in which a local path (trajectory) of a moving body according to an embodiment is configured by combining a clothoid curve and a curvature change point. FIG. 1 is a diagram illustrating a cost function according to an embodiment. 1 is a flowchart showing a series of operations in a travel control process for a moving body according to an embodiment; 1 is a flowchart showing a series of operations for trajectory generation and control variable determination according to an embodiment. FIG. 10 is a diagram illustrating a first example of determining the maximum value of curvature based on a generated trajectory. FIG. 10 is a diagram illustrating a second example of determining the maximum curvature value based on a generated trajectory. FIG. 10 is a diagram illustrating a third example of determining the maximum value of curvature based on a generated trajectory. 1 is a flowchart showing a series of operations related to determining a control amount according to an embodiment;

The following embodiments are described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the scope of the claimed invention, and not all combinations of features described in the embodiments are necessarily essential to the invention. Two or more of the features described in the embodiments may be combined in any desired manner. Furthermore, the same reference numbers are used for identical or similar components, and duplicate descriptions will be omitted.

In the following embodiment, an ultra-compact electric vehicle with a passenger capacity of approximately one person will be described as an example of a mobile body that is micromobility. However, micromobility may also include vehicles that travel with people, carrying luggage instead of passengers. Furthermore, this embodiment is not limited to examples in which the mobile body is an electric vehicle, and can also be applied to mobile bodies other than electric vehicles. Furthermore, in the following description, an example of a mobile body with one driven wheel will be described, but it does not necessarily have to have a driven wheel, and the number of driven wheels is not limited to one, but may be two or more.

For mobile vehicles such as the micromobility mentioned above, it would be useful to realize autonomous driving that takes into account the presence of people, the frequent changes in target location, and the lack of high-precision maps. Micromobility does not necessarily travel along specific, fixed routes, and must be able to travel in both areas where automobiles and pedestrians are mobile, so it must be able to navigate areas where high-precision maps are not available. Furthermore, when traveling through shopping malls or event venues, for example, it is necessary to navigate while appropriately avoiding obstacles in situations where multiple obstacles are present at irregular intervals. Furthermore, when people ride in micromobility, unlike unmanned delivery robots, there is a risk that passengers will feel uneasy if an unnatural driving trajectory or a driving trajectory that does not take into account the ride comfort is adopted.

The mobile body 100 according to this embodiment autonomously travels toward a target position while avoiding obstacles without using a high-precision map. Because it travels autonomously without using a high-precision map, the areas in which the mobile body 100 can travel are identified using information recognized from the output of a detection unit, which will be described later. As will be described later, the mobile body 100 generates a grid map that indicates areas in which the mobile body 100 can travel and areas in which it cannot travel, and uses this to generate a trajectory for the mobile body 100. Furthermore, the mobile body 100 generates a trajectory with a high degree of freedom and that takes into consideration ride comfort, using a clothoid curve with points where the curvature changes nonlinearly (hereinafter simply referred to as curvature change points). The mobile body 100 controls its drivetrain so that it travels along the generated trajectory.

<Configuration of moving body>
The configuration of the moving body 100 will be described with reference to Fig. 1. Fig. 1(A) shows a side view of the moving body 100 according to this embodiment, and Fig. 1(B) shows the internal configuration of the moving body 100. In the figure, arrow X indicates the front-to-rear direction of the moving body 100, with F indicating the front and R indicating the rear. Arrows Y and Z indicate the width direction (left-to-right direction) and up-down direction of the moving body 100.

The mobile body 100 is an electric autonomous vehicle equipped with a propulsion unit 112 and powered by a battery 113 as its main power source. The battery 113 is a secondary battery such as a lithium-ion battery, and the mobile body 100 is propelled by the propulsion unit 112 using power supplied from the battery 113. The propulsion unit 112 is in the form of a tricycle equipped with a pair of front drive wheels 120 (left and right) and a single rear driven wheel 121. The propulsion unit 112 may also be in the form of a four-wheeled vehicle or other form. The mobile body 100 is equipped with, for example, a single seat 111.

The traveling unit 112 is equipped with a drive mechanism 122. The drive mechanism 122 uses motors 122a and 122b as drive sources to rotate the corresponding drive wheels 120. The drive mechanism 122 can move the mobile body 100 forward or backward by rotating each of the drive wheels 120. The drive mechanism 122 can also change the direction of travel of the mobile body 100 by generating a difference in rotation between motors 122a and 122b. The traveling unit 112 is equipped with a driven wheel 121. The driven wheel can rotate around the Z direction as its rotation axis.

The mobile object 100 is equipped with detection units 114-116 that detect targets around the mobile object 100. The detection units 114-116 are a group of external sensors that monitor the surroundings of the mobile object 100. In this embodiment, the detection units 114-116 are all imaging devices that capture images of the surroundings of the mobile object 100, and are equipped with, for example, an optical system such as a lens and an image sensor. However, radar or lidar (light detection and ranging) may be used instead of or in addition to the imaging devices.

Two detection units 114 are arranged, for example, at the front of the moving body 100, spaced apart in the Y direction, and are primarily used to detect targets ahead of the moving body 100. Detection units 115 are arranged on the left and right sides of the moving body 100, respectively, and are primarily used to detect targets to the sides of the moving body 100. Detection unit 116 is arranged at the rear of the moving body 100, and is primarily used to detect targets behind the moving body 100.

Figure 2 is a block diagram of the control system of the mobile object 100. The mobile object 100 is equipped with a control unit (ECU) 130. The control unit 130 includes one or more processors, such as a CPU, a memory device such as a semiconductor memory, an interface with external devices, etc. The memory device stores programs executed by the processor and data used for processing by the processor. Multiple sets of processors, memory devices, and interfaces may be provided for different functions of the mobile object 100 and configured to be able to communicate with each other.

The control unit 130 acquires output (e.g., image information) from the detection units 114-116, input information from the operation unit 131, and audio information input from the audio input device 133, and performs processing according to the respective information. The control unit 130 controls the motors 122a and 122b (driving control of the driving unit 112), controls the display of the display panel included in the operation unit 131, and outputs audio alerts and information to the occupants of the vehicle 100. The control unit 130 may process output (e.g., image information) from the detection units 114-116 using a machine learning model for image recognition (e.g., a deep neural network). The control unit 130 may also process output (e.g., audio information) from the audio input device 133 using a machine learning model for voice recognition (e.g., a deep neural network).

The audio input device 133 includes, for example, a microphone, and picks up the voices of the occupants of the vehicle 100. The control unit 130 is able to recognize the input voices and perform corresponding processing. The GNSS (Global Navigation Satellite system) sensor 134 receives GNSS signals and detects the current position of the vehicle 100.

The storage device 135 includes a non-volatile recording medium that stores various data. The storage device 135 may also store programs executed by the processor, data used by the processor for processing, etc. The storage device 135 may also store various parameters (e.g., trained parameters and hyperparameters of a deep neural network) of machine learning models for speech recognition and image recognition executed by the control unit 130.

The communication device 136 is a communication device capable of communicating with an external device (e.g., a communication terminal 140 owned by a user) via wireless communication such as Wi-Fi or fifth-generation mobile communication.

Next, an example of the functional configuration of the control unit 130 will be described with reference to Figure 3. The user instruction acquisition unit 301 acquires user instructions input via the operation unit 131 or the voice input device 133. The user instructions include a specification of a final target position where the mobile object 100 should arrive. The final target position may be the position of a target specified by spoken voice among targets recognized in the images output by the detection units 114 to 116. The user instructions may also include an instruction to change the traveling trajectory of the mobile object 100, such as turning right or left, while the mobile object 100 is traveling.

The image information processing unit 302 recognizes the position, shape, etc. of the roadway and obstacles based on the output (e.g., image information) of the detection units 114-116. Recognition of the roadway ahead of the mobile object 100 and the position, shape, etc. of obstacles is performed, for example, by calculating the depth distance from the mobile object 100 using stereo images obtained from the two detection units 114. To recognize the roadway and obstacles, a pre-trained machine learning model for image recognition (e.g., a deep neural network) may be used on monocular or stereo images.

The grid map generation unit 303 generates a grid map that indicates areas near the mobile body 100 that are drivable and areas that are not drivable for the mobile body 100, based on the driving path and the positions and shapes of obstacles recognized by the image information processing unit 302. Figure 4 schematically shows an example of a grid map according to this embodiment. The example shown in Figure 4 schematically shows how the detection unit 403 captures an image of the area ahead of the mobile body 402, and generates a grid map 400 that indicates an impassable area 401 indicating the presence of an obstacle, and other areas (drivable areas).

The grid map generation unit 303 shifts the grid map 400 as the mobile object 100 moves so that the mobile object is positioned at the center of the grid map. The grid map generation unit 303 assigns the undrivable areas 401 to the corresponding grids of the grid map 400 according to the recognition results of the image information processing unit 302. For example, if the grid map generation unit 303 recognizes that an object exists at a predetermined height from the ground (e.g., a height at which the mobile object 100 cannot proceed), it designates the area corresponding to the position where the object is recognized as an undrivable area. The grid map generation unit 303 generates the grid map by adding undrivable areas 401 as the mobile object 100 moves.

The path generation unit 304 generates a path (travel path) for the mobile body 100 by executing the processes of trajectory generation and control variable determination described below. The travel path generated by the path generation unit 304 in this embodiment may be referred to as a local path, as opposed to a global path described below. The path generation unit 304 can generate a path based on the target position by referencing the global path. The global path is a path toward the target position that roughly determines the travel path of the mobile body. In this embodiment, the path generation unit 304 may generate the global path by any method, including publicly known methods. The target position differs from the final target position specified by the user, but is a temporary position to be reached when the travel path of the mobile body 100 is determined at regular intervals. The target position is set on the global path. The maximum distance from the mobile body's position to the target position may be set according to the range within which obstacles can be detected by the detection unit, such as 6 meters. That is, the path generation unit 304 can limit the traveling trajectory to a range within which the mobile body can adequately detect obstacles, etc. Furthermore, the maximum distance from the mobile body's current position to the target position may be set, for example, according to the braking distance within which the mobile body 100 can control its traveling in an emergency. That is, the path generation unit 304 can limit the traveling trajectory to a range within which it is adequately possible to control the mobile body 100, such as by stopping it. Furthermore, the closer the target position is to the final target position (e.g., the position of a target specified by the user), the closer the target position is set to the mobile body.

To generate a driving trajectory, the path generation unit 304 generates a trajectory composed of a combination of multiple clothoid curves and curvature change points where the curvature changes nonlinearly. A clothoid curve is a curve where the curvature of the trajectory changes linearly with distance. A clothoid curve is also generally known as the trajectory drawn by a vehicle equipped with a steering wheel when the steering wheel is turned at a constant rate while traveling at a constant speed. In this embodiment, by combining multiple trajectories where the curvature of each trajectory changes linearly with curvature change points where the curvature changes nonlinearly, a complex trajectory with a high degree of freedom, such as snaking left and right, can be generated. In other words, such a trajectory makes it possible to avoid obstacles by snaking left and right, even when there are multiple obstacles.

Furthermore, by configuring the above trajectory, it is possible to generate a trajectory for a vehicle equipped with a steering wheel, for example, by turning the steering wheel at a constant rate, passing through a curvature change point, and then turning the steering wheel in a different constant manner. In other words, even when generating a trajectory with a high degree of freedom, the curvature of the trajectory changes smoothly, ensuring a comfortable ride for passengers riding in the moving body. By adjusting the curvature at three points on the trajectory, the path generation unit 304 can suppress frequent changes in the turning direction of the moving body 100 and further consider motion constraints of the moving body 100, such as the minimum turning radius.

Figure 5 shows a schematic example of a trajectory 503 traveled by a moving object 501. An obstacle 502 exists ahead of the moving object 501 in the direction of travel (X direction). The Y direction indicates the left-right direction relative to the moving object's direction of travel. The trajectory 503 is composed of multiple clothoid curves and multiple curvature change points 504-506. As described above, the multiple clothoid curves and curvature change points allow the path generation unit 304 to generate a traveling trajectory 503 that does not deviate significantly from the global path 507 (shown as a point cloud), even if the global path 507 is a complex path. Note that S1 to S3 indicate the distance between adjacent curvature change points 504-506. This distance may be equally spaced, or an optimal distance determined in advance through experimentation or the like may be set.

Figure 6A shows the relationship between the distance from the moving body and the curvature of the trajectory for generating the trajectory 503. As shown in Figure 6A, the trajectory 503 generated in this embodiment has a constant curvature (i.e., a linear change) up to the maximum or minimum point of the curvature (the point of change of the curvature).

In this embodiment, an example is described in which the curvatures of the trajectory (curvatures _K1 , _K2 , and _K3 ) at the positions of three curvature change points on the trajectory are optimized. While it is possible to use more curvature change points, increasing the number of curvature change points to be adjusted can dramatically increase the amount of calculations required for optimization using a cost function, which will be described later. In other words, the amount of calculations increases significantly compared to the improvement in the degree of freedom of the resulting traveling trajectory. By using three curvature change points, the path generation unit 304 can generate a traveling trajectory with a high degree of freedom while reducing the amount of calculations required for optimization. By appropriately reducing the number of curvature change points, it becomes possible to repeat the generation of the traveling trajectory in a shorter cycle (e.g., in real time).

An overview of the trajectory generation process performed by the path generation unit 304 will be described. The path generation unit 304 substitutes the trajectory with the curvatures changed at three points into a cost function and determines the curvature at the curvature change point that reduces the cost according to the cost function. The cost function is expressed as shown in Equation (1), where C _poserr is the cost of deviation from the global path, C _obstacle is the cost of approaching or colliding with the obstacle, and C _oscillation is the cost of difference from the trajectory generated at the previous time. The cost of deviation from the global path references the global path (i.e., information indicating a predetermined reference trajectory of the mobile object 100), and the cost increases as the generated trajectory deviates from the reference trajectory. Therefore, even when generating a trajectory with a high degree of freedom, it is possible to generate a trajectory that does not deviate significantly from the reference trajectory. Furthermore, the cost of difference from the trajectory generated at the previous time decreases as the difference (position deviation) from the trajectory generated at the previous time decreases. In other words, the path generation unit 304 references a trajectory generated a predetermined time ago and determines the curvatures of multiple curvature change points using a cost function in which the cost increases the greater the amount of change between the trajectory to be generated and the trajectory generated a predetermined time ago. Therefore, by using the cost of difference from the trajectory generated immediately before (e.g., the time immediately before), it is possible to suppress sudden changes in the trajectory. The path generation unit 304 selects curvatures _K1 , _K2 , and _K3 that minimize the cost function of equation (1). For example, curvature _K1 corresponds to the curvature at curvature change point 601, curvature _K2 corresponds to the curvature at curvature change point 602, and curvature _K3 corresponds to the curvature at curvature change point 603. The costs (C _poserr , C _obstacle , C _oscillation ) constituting equation (1) are calculated according to equations (2) to (4). Note that t corresponds to the current timing, and t-1 indicates the timing at which the previous trajectory was calculated.

FIG. 6B schematically illustrates the cost function according to this embodiment, which is represented by equation (1). For example, the deviation cost from the global path, C _poserr , is calculated by calculating the trajectory to be generated and the value obtained by assigning the potential of the global path to a grid. For example, the potential of the global path is assigned such that a higher cost is assigned to a grid the farther the grid is from the global path. By using such a potential, the curvature change point is optimized so that the trajectory to be generated approaches the global path. Furthermore, the cost of approaching or colliding with an obstacle, C _obstacle , is calculated by calculating the trajectory to be generated and the value obtained by assigning the potential of the obstacle to a grid. For example, the closer the obstacle is to a non-travelable area of the grid map, the higher the cost is assigned to the potential of the obstacle. By using such a potential, the curvature change point is optimized so that the trajectory to be generated avoids the obstacle.

When varying the curvature at a curvature change point, the path generation unit 304 performs Adam optimization using the loss gradient to determine the curvature at the (next) curvature change point in the iterative calculation. _{β 1} , β ₂ , and ε are parameters that can be determined in advance through experiments or the like for optimization. t corresponds to the current timing, where t-1 indicates the previous calculation timing in the iterative calculation, and ▽L indicates the differential value of the cost function. K _t corresponds to the current curvature at any of the curvature change points.

The path generating unit 304 repeatedly calculates the cost shown in Equation 1 using the trajectory generated by varying the curvature at the curvature change points, and determines the curvatures K ₁ , K ₂ and K ₃ that result in the lowest cost L.

In the example shown in Figure 6B, a cost grid is used to represent the potential of a global route and the potential of an obstacle. The cost grid may be composed of the same number of grids as the grid map. As described above, each grid in the cost grid is associated with a cost value corresponding to the distance from the global route and the distance from the obstacle. Multiple cost grids can be taken into account by, for example, adding up the values of corresponding grids. In a cost grid that handles the potential of a global route, for example, when a global route is projected onto a grid surface, a lower cost value is set for grids closer to the global route. The route generation unit 304 stores the set cost grid in a memory device, and when a candidate trajectory is generated, it projects the traveling trajectory onto the cost grid and adds up the cost values of grids that overlap with the traveling route. This process enables relatively simple calculations to speed up the optimization calculation for generating a trajectory.

Furthermore, the path generation unit 304 performs a process of determining control variables using the determined trajectory to determine the speed v and angular velocity ω, which serve as control variables for controlling the traveling of the mobile body. The process of determining control variables is a process of determining the speed v and angular velocity ω so as to satisfy predetermined constraints when traveling along the generated trajectory. The predetermined constraints, as will be described in detail later, are, for example, constraints imposed to enable the mobile body 100 to safely turn curves or to ensure a stable and comfortable ride.

The driving control unit 305 controls the driving of the mobile body 100 (e.g., controls motors 122a and 122b) in accordance with the control determined by the path generation unit 304.

<A series of operations in the travel control process of the moving body 100>
Next, a series of operations in the travel control process of the mobile body 100 will be described with reference to Fig. 7. This process is realized by the control unit 130 expanding a program stored in the storage device 135 into the memory device of the control unit 130 and executing it. At the start of this process, it is assumed that a final destination position has been set in accordance with a user instruction or the like.

At S701, the image information processing unit 302 of the control unit 130 acquires the output (image information) of the detection units 114 to 116. The image information processing unit 302 recognizes the position and shape of the road and obstacles contained in the image information, for example, using a deep neural network.

In S702, the grid map generation unit 303 of the control unit 130 generates the grid map described with reference to FIG. 4. As described above, the grid map generation unit 303 generates a grid map that indicates areas in the vicinity of the mobile object 100 that the mobile object 100 can travel in and areas that the mobile object 100 cannot travel in, based on the travel path and the position and shape of obstacles recognized by the image information processing unit 302.

In S703, the path generation unit 304 of the control unit 130 acquires a global path. As described above, the global path may be generated in any manner as long as it roughly determines the trajectory of the moving object. The path generation unit 304 may use, for example, the A* algorithm to generate a global path that does not collide with obstacles on the grid map.

In S704, the path generation unit 304 of the control unit 130 generates a path (local path) along which the moving object will travel, including a clothoid curve, as described above. The process of generating the travel path in this step will be described later with reference to Figure 8.

In S705, the path generation unit 304 of the control unit 130 generates a control amount for the moving body 100 based on the generated trajectory. The process of determining the control amount in this step will be described later with reference to Figure 8.

In S706, the driving control unit 305 of the control unit 130 controls the motors 122a and 122b using the control variables (velocity v and angular velocity ω) determined by the path generation unit 304, thereby controlling the driving of the mobile body 100.

In S707, the control unit 130 determines whether the final target position has been reached. If the control unit 130 determines that the final target position has not been reached, the process returns to S701 and is repeated. If the control unit 130 determines that the final target position has been reached, this series of processes ends.

<A series of operations for generating a trajectory of the moving body 100 and determining a control amount>
Next, a series of operations for trajectory generation and control variable determination processing executed by the path generation unit 304 will be described. This processing is realized by the control unit 130 loading a program stored in the storage device 135 into the memory device of the control unit 130 and executing it. In this processing, steps S801 and S802 are executed in S704, and then step S803 is executed in S705.

In S801, the path generation unit 304 calculates the initial curvature of the curvature change point of the clothoid curve using the global path. Specifically, the path generation unit 304 first generates a path similar to the global path without considering the presence of obstacles, and provides an initial path for path generation in the next step. The path generated in this step corresponds to performing an optimization calculation using only C _poserr in the above-mentioned equation (1) to calculate the curvature of the curvature change point. The path generation unit 304 may use only C _poserr and C _oscillation . By performing the processing in this step, it is possible to reduce the possibility that the curvature determined in the optimization calculation in S802 will fall into a local solution, and it is possible to obtain an optimal solution with higher accuracy.

In S802, the path generation unit 304 calculates the curvature change points of the clothoid curve using the global path, the grid map, and the past path. That is, the path generation unit 304 calculates the curvatures at, for example, three curvature change points (generates a trajectory) using the costs (C _poserr , C _obstacle , C _oscillation ) constituting the above-mentioned equation (1) by the above-mentioned method.

In S803, the path generating unit 304 determines a combination of a target speed and a target angular speed based on the generated trajectory. Specifically, the path generating unit 304 determines a speed _vmax at the start of the control amount determination process by referring to the generated trajectory. Then, the path generating unit 304 performs the control amount determination process described below.

9A to 9C show examples of determining the curvature with the largest absolute value within a predetermined curvature reference range for a trajectory determined by curvature change points 601 to 603. In the example of FIG. 9A, the path generation unit 304 determines curvature 902 as the curvature _Kmax with the largest absolute value within the curvature reference range from the position of the mobile object to a distance 901. In the example of FIG. 9B, the path generation unit 304 determines curvature 911 as the curvature Kmax with the largest absolute value within the curvature reference range from the position of the mobile object to a distance 901. Furthermore, in the example of FIG. 9C, the path generation unit 304 determines curvature 921 as _the curvature _Kmax with the largest absolute value within the curvature reference range from the position of the mobile object to a distance 901. In this way, by referring to the curvature with the largest absolute value, when the curvature of the generated trajectory is determined to be heading toward or traveling along a sharp curve, the path generation unit 304 performs control to reduce the speed and angular velocity through subsequent processing. 9A to 9C, the path generating unit 304 determines v _max according to v _max = ω _max / K _max , where ω _max may be determined in advance based on the characteristics of the moving object 100, etc.

The path generation unit 304 may vary the curvature reference range depending on the current speed or deceleration of the moving body 100. For example, the path generation unit 304 may narrow the curvature reference range when the current speed of the moving body 100 is high. In other words, when the current speed of the moving body 100 is high, the path generation unit 304 imposes stronger constraints on the selection of speed and angular velocity, thereby providing safety and a stable ride.

Next, the control variable determination process performed by the path generation unit 304 will be described with reference to Figure 10. Note that this process is realized by the control unit 130 expanding a program stored in the storage device 135 into the memory device of the control unit 130 and executing it.

In S1001, the path generating unit 304 substitutes _vmax for the reference velocity _vref to obtain _vref , and then determines the reference angular velocity _ωref in accordance with _ωref ← _vref * _Kref . Note that the reference curvature _Kref is a value obtained by referencing up to the tip of the trajectory depending on the magnitude of the velocity of the moving body 100, for example.

In S1002, the path generation unit 304 determines whether the acceleration of the moving body is equal to or less than a predetermined acceleration (translational acceleration of 0.1 G or less) under the conditions of the reference velocity and reference angular velocity. If the acceleration is equal to or less than the predetermined acceleration, the path generation unit 304 proceeds to S1004, and if not, the path generation unit 304 proceeds to S1003. In S1003, the path generation unit 304 changes _vref (slows down) so that it falls within the predetermined acceleration of S1002.

In S1004, the path generation unit 304 determines whether the deceleration of the moving object is equal to or less than a predetermined deceleration (deceleration of 0.01 G or less) under the conditions of the reference velocity and the reference angular velocity. If the deceleration is equal to or less than the predetermined deceleration, the path generation unit 304 proceeds to S1006; otherwise, the path generation unit 304 proceeds to S1005. In S1005, the path generation unit 304 changes _vref so that the deceleration falls within the predetermined deceleration of S1004.

In S1006, the path generation unit 304 determines whether the absolute value of the angular velocity of the moving body is equal to or less than a predetermined angular velocity (|ω _ref |≦|ω _max | or less) under the conditions of the reference velocity and reference angular velocity. If the deceleration is equal to or less than the predetermined deceleration acceleration, the path generation unit 304 proceeds to S1008, and if not, proceeds to S1007. In S1007, the path generation unit 304 changes v _ref so that |ω _ref | satisfies the predetermined angular velocity.

In S1008, the path generation unit 304 determines whether the acceleration in the left-right direction of the moving object (a _y =ω _ref *v _ref ) is equal to or less than a predetermined value. If the acceleration in the left-right direction is equal to or less than the predetermined value, the path generation unit 304 proceeds to S1009, and if not, proceeds to S1007.

In S1009, the path generating unit 304 determines the calculated reference velocity v _ref and reference angular velocity ω _ref as control variables (target velocity v and target angular velocity ω). The path generating unit 304 then ends this process and returns to the process of S803. After completing the process of S803, the path generating unit 304 ends the series of processes shown in FIG. 8.

As explained above, in the above-described embodiment, the trajectory on which the mobile body 100 should travel is generated using a trajectory formed by combining multiple trajectories (i.e., clothoid curves) whose curvatures change linearly with distance and curvature change points whose curvatures change nonlinearly. This makes it possible to generate a travel trajectory with a high degree of freedom while ensuring a comfortable ride. Furthermore, in this embodiment, the target speed and target angular velocity of the mobile body (i.e., the control amount of the mobile body) are determined based on the generated trajectory (e.g., curvature within a predetermined range) so that the acceleration and angular velocity satisfy certain conditions. This further enables control of the mobile body with consideration for safety and comfort, and reduces the load on the occupant caused by acceleration and turning.

The configuration of the control unit 130 described above may function in various forms as a mobile object control system. For example, a mobile object control system may be configured in such a manner that at least a portion of the control unit 130 described above is configured on a device external to the mobile object 100, such as an external server. Alternatively, the mobile object control system may be the mobile object 100, or may be configured to be incorporated within the mobile object 100 (i.e., the control unit 130). Furthermore, the computer program that operates the mobile object 100 described above may be a computer program that causes one or more computers to function as each means of the mobile object control system.

<Summary of the embodiment>
1. The mobile object control system for controlling the operation of the mobile object (e.g., 100) of the above embodiment includes:
a generation means (e.g., 304) for generating a trajectory along which the moving object should travel, using a trajectory from the position of the moving object to a target position, the trajectory being formed by combining a plurality of trajectories, each of which has a curvature that changes linearly with distance, and a curvature change point, the curvature of which changes nonlinearly;
and a determining means (e.g., 304) for determining a control amount for controlling the traveling of the moving body based on the generated trajectory.

This embodiment makes it possible to generate a highly flexible running trajectory while ensuring a comfortable ride.

2. In the mobile object control system according to the above embodiment,
the trajectory along which the moving body should travel includes a plurality of curvature change points,
The generating means determines the curvatures at the plurality of curvature change points to generate a trajectory along which the moving body should travel.

According to this embodiment, even when generating a trajectory with a high degree of freedom, the curvature of the trajectory changes smoothly, ensuring a comfortable ride for passengers on the moving body.

3. In the mobile object control system according to the above embodiment,
The generation means refers to information indicating the location of an obstacle and determines the curvature of the multiple curvature change points using a cost function in which the cost increases as the position of the trajectory to be generated approaches the location of the obstacle.

This embodiment makes it possible to generate a trajectory that appropriately avoids obstacles, even when generating a trajectory with a high degree of freedom.

4. In the mobile object control system according to the above embodiment,
The generation means refers to information indicating a predetermined reference trajectory of the moving body and determines the curvatures of the multiple curvature change points using a cost function in which the cost increases the more the generated trajectory deviates from the reference trajectory.

This embodiment makes it possible to generate a trajectory that does not deviate significantly from the reference trajectory, even when generating a trajectory with a high degree of freedom.

5. In the mobile object control system according to the above embodiment,
The generation means refers to a trajectory on which the moving body should travel that was generated a predetermined time ago, and determines the curvatures of the multiple curvature change points using a cost function in which the cost increases the greater the amount of change in the trajectory to be generated from the trajectory on which the moving body should travel that was generated the predetermined time ago.

This embodiment makes it possible to suppress sudden changes in trajectory even when generating trajectories with a high degree of freedom.

6. In the mobile object control system according to the above embodiment,
The trajectory along which the moving body should travel has three curvature change points.

This embodiment makes it possible to generate a highly flexible driving trajectory while reducing the amount of calculation required for optimization.

7. In the mobile object control system according to the above embodiment,
The determining means calculates the velocity and angular velocity of the moving body, which are the control variables, based on the largest curvature of the generated trajectories.

This embodiment makes it possible to determine the control amount that best follows the generated trajectory while satisfying constraints related to safety and ride comfort.

8. In the mobile object control system according to the above embodiment,
The determination means determines the velocity and angular velocity of the moving body, which are the control variables, based on the largest curvature of the generated trajectory within a predetermined range that varies depending on the current velocity of the moving body.

This embodiment places stronger constraints on the selection of speed and angular velocity, making it possible to provide safety and a stable ride.

9. In the mobile object control system according to the above embodiment,
When the velocity and angular velocity of the moving body do not satisfy the constraints for the moving body to travel stably, the determining means changes the velocity and angular velocity of the moving body so as to satisfy the constraints.

This embodiment makes it possible to control a moving vehicle with consideration for safety and ride comfort, and reduces the load on the occupant caused by acceleration and turning.

10. In the mobile object control system according to the above embodiment,
The vehicle further includes a detection means for detecting a position where an obstacle exists based on an image captured by the imaging means of the vehicle,
The maximum distance to the target position is set according to the range within which the detection means can detect an obstacle.

This embodiment allows the moving object's travel trajectory to be limited to a range where obstacles, etc. can be adequately detected.

11. In the mobile object control system according to the above embodiment,
The maximum distance to the target position is set in accordance with a braking distance that allows the travel of the moving body to be controlled.

According to this embodiment, the travel trajectory of the moving body 100 can be limited to a range that allows sufficient control, such as stopping, of the moving body 100.

The invention is not limited to the above-described embodiments, and various modifications and variations are possible within the scope of the invention.

100...mobile vehicle, 120...drive wheels, 121...driven wheels, 130...control unit, 303...grid map generator, 304...route generator, 305...travel control unit

Claims (14)

A mobile object control system for controlling the operation of a mobile object,
a generation means for generating a trajectory along which the moving object should travel, using a trajectory from the position of the moving object to a target position, the trajectory being formed by combining a plurality of trajectories, each of which has a curvature that changes linearly , and a plurality of curvature change points, each of which has a curvature that changes nonlinearly;
a determination means for determining a control amount for controlling the traveling of the moving body based on the generated trajectory ,
a generation means for generating a trajectory on which the moving body should travel by substituting a trajectory in which the curvatures of the plurality of curvature change points are changed into a cost function to calculate a cost using the cost function, and repeatedly changing the curvatures of the plurality of curvature change points using a gradient of the cost function so as to reduce the cost, thereby determining the curvatures of the plurality of curvature change points . 2. The mobile body control system according to claim 1, wherein the generation means refers to information indicating a position where an obstacle is present, and determines the curvatures of the plurality of curvature change points using a cost function in which the cost increases as the position of the trajectory to be generated approaches the position where the obstacle is present. 2. The mobile body control system according to claim 1, wherein the generation means refers to information indicating a predetermined reference trajectory of the mobile body, and determines the curvatures of the plurality of curvature change points using a cost function in which the cost increases the more the generated trajectory deviates from the reference trajectory. 2. The mobile body control system according to claim 1, wherein the generation means refers to a trajectory on which the mobile body should travel that was generated a predetermined time ago, and determines the curvatures of the plurality of curvature change points using a cost function in which the cost increases the greater the amount of change in the trajectory to be generated from the trajectory on which the mobile body should travel that was generated the predetermined time ago . 2. The mobile object control system according to claim 1 , wherein the trajectory along which the mobile object is to travel has three curvature change points. The mobile body control system described in claim 1, characterized in that the determination means calculates the velocity and angular velocity of the mobile body, which are the control variables, based on the largest curvature among the curvatures of the generated trajectories. The mobile body control system according to claim 6, wherein the determining means determines the velocity and angular velocity of the mobile body, which are the control variables, based on the largest curvature of the generated trajectory within a predetermined range that varies depending on the current velocity of the mobile body. 7. The mobile body control system according to claim 6, wherein, when the velocity and angular velocity of the mobile body do not satisfy constraints for the mobile body to travel stably, the determining means changes the velocity and angular velocity of the mobile body so as to satisfy the constraints. The vehicle further includes a detection means for detecting a position where an obstacle exists based on an image captured by the imaging means of the vehicle,
2. The mobile object control system according to claim 1, wherein the maximum distance to the target position is set in accordance with a range within which the detection means can detect an obstacle. The mobile object control system of claim 1, wherein the maximum distance to the target position is set according to a braking distance that allows control of the traveling of the mobile object. A mobile object,
a generation means for generating a trajectory along which the moving object should travel, using a trajectory from the position of the moving object to a target position, the trajectory being formed by combining a plurality of trajectories, each of which has a curvature that changes linearly , and a plurality of curvature change points, each of which has a curvature that changes nonlinearly;
a determination means for determining a control amount for controlling the traveling of the moving body based on the generated trajectory ,
the generation means substitutes the trajectory in which the curvatures of the plurality of curvature change points are changed into a cost function to calculate a cost using the cost function, and repeatedly changes the curvatures of the plurality of curvature change points using a gradient of the cost function so as to reduce the cost, thereby determining the curvatures of the plurality of curvature change points and generating a trajectory on which the moving body should travel . A control method for a mobile object control system for controlling the operation of a mobile object, comprising:
a generation step of generating a trajectory along which the moving object should travel, using a trajectory from the position of the moving object to a target position, the trajectory being formed by combining a plurality of trajectories, each of which has a curvature that changes linearly , and a plurality of curvature change points, each of which has a curvature that changes nonlinearly;
a determination step of determining a control amount for controlling the traveling of the moving object based on the generated trajectory ,
a control method for a mobile body control system, characterized in that in the generation step, a trajectory in which the curvatures of the plurality of curvature change points are changed is substituted into a cost function to calculate a cost using the cost function, and the curvatures of the plurality of curvature change points are repeatedly changed using a gradient of the cost function so as to reduce the cost, thereby determining the curvatures of the plurality of curvature change points and generating a trajectory on which the mobile body should travel . A program for causing a computer to function as each of the means of the mobile object control system according to any one of claims 1 to 10 . A recording medium storing a program for causing a computer to function as each of the means of the mobile object control system according to any one of claims 1 to 10 .