Method, system, device and computer-readable storage medium for identifying accessibility

Abstract

Provided are a method, system, device and computer-readable storage medium for identifying accessibility, the method comprising: (S201) setting a plurality of simulation units, each of which can simulate the movement of a moving object; (S202) recording the access frequency of each grid in a pre-generated grid map generated by the plurality of simulation units during the process of simulating the movement of the moving object, and obtaining access frequency information; wherein the grid map is used to describe information about the surrounding environment of the moving object; (S203) determining the accessibility of the surrounding environment of the moving object based on the access frequency information. The method can improve the accuracy of identifying accessibility.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of unmanned driving, and in particular, to a method, system, device and computer-readable storage medium for identifying passability. Background Art

[0002] In autonomous driving, sensors are mainly used to obtain information about the surrounding environment, and then a description of the surrounding environment, that is, the passability of the surrounding environment, is calculated and analyzed to provide decisions for autonomous driving planning.

[0003] At present, the analysis of passability mainly involves local passability analysis of 2.5D maps, determining the passability of each grid in a small range in a binary description, and then globally performing connected clustering of grids with "passable" passability. Finally, filtering out the smaller fragments after clustering, marking their attributes as "unknown" or "inaccessible", and marking the attributes of the remaining "passable" grids obtained by clustering as "passable". In the connectivity stage, this processing method treats the 2.5D map as a binary image, and only considers whether the passable area is connected. However, in fact, autonomous driving vehicles have a minimum pass size, and openings smaller than the minimum pass size cannot be passed by the vehicle even if they are physically connected. In addition, since the results of the local passability analysis are binary, it is also impossible to predict the "reaching cost" of a certain connected area. In summary, the recognition accuracy of passability in the prior art is not high. Summary of the invention

[0004] Embodiments of the present invention provide a method, system, device and computer-readable storage medium for identifying passability, so as to improve the accuracy of identifying passability.

[0005] A first aspect of an embodiment of the present invention is to provide a method for identifying accessibility, comprising: setting up multiple simulation units, each of which can simulate the movement of a moving object; recording the access frequency of each grid in a pre-generated grid map by the multiple simulation units in the process of simulating the movement of the moving object, and obtaining access frequency information; wherein the grid map is used to describe information about the surrounding environment of the moving object; and determining the accessibility of the surrounding environment of the moving object based on the access frequency information.

[0006] The second aspect of an embodiment of the present invention is to provide a system for identifying accessibility, comprising: a memory and a processor; the memory is used to store program code; the processor calls the program code, and when the program code is executed, is used to perform the following operations: setting multiple simulation units, each of which can simulate the movement of a moving object; recording the access frequency of each grid in a pre-generated grid map generated by the multiple simulation units in the process of simulating the movement of the moving object, and obtaining access frequency information; wherein the grid map is used to describe information about the surrounding environment of the moving object; and determining the accessibility of the surrounding environment of the moving object based on the access frequency information.

[0007] A third aspect of an embodiment of the present invention is to provide a movable platform, comprising:

[0008] body;

[0009] A power system, installed on the fuselage, for providing movement power;

[0010] And the method described in the first aspect.

[0011] A fourth aspect of an embodiment of the present invention is to provide a computer-readable storage medium on which a computer program is stored, and the computer program is executed by a processor to implement the method described in the first aspect.

[0012] The method, system, device and computer-readable storage medium for identifying passability provided in this embodiment are configured by setting a plurality of simulation units, each of which can simulate the movement of a moving object; recording the access frequency of each grid in a pre-generated grid map of the plurality of simulation units in the process of simulating the movement of the moving object, and obtaining access frequency information; wherein the grid map is used to describe the information of the surrounding environment of the moving object; and determining the passability of the surrounding environment of the moving object according to the access frequency information. Since the simulation units configured can simulate the movement process of the moving object on the ground, and the simulated movement process of the simulation units is represented by the access frequency information, the passability of the vehicle in the surrounding environment can be intuitively understood, thereby providing a basis for the decision-making of the automatic driving path planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0014] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present invention;

[0015] Figure 2 A flow chart of a method for identifying feasibility provided by an embodiment of the present invention;

[0016] Figure 3 A schematic diagram of the size attributes of a simulation unit provided by an embodiment of the present invention;

[0017] Figure 4 A schematic diagram of a preset step length provided in an embodiment of the present invention;

[0018] Figure 5 A schematic diagram of the rebound direction after a collision provided by an embodiment of the present invention;

[0019] Figure 6 A schematic diagram of a neighborhood grid provided by an embodiment of the present invention;

[0020] Figure 7 A schematic diagram of sports mileage provided by an embodiment of the present invention;

[0021] Figure 8 A flowchart of a method for identifying feasibility provided by another embodiment of the present invention;

[0022] Fig. 9 This is a diagram of feasibility recognition results in the prior art.

[0023] Fig.10 This is the access frequency information obtained by using the method in the embodiment of the present invention.

[0024] Fig.11 A feasibility recognition result diagram obtained by using the method of an embodiment of the present invention;

[0025] Fig.12 A structural diagram of a feasibility identification system provided in an embodiment of the present invention.

[0026] Reference numerals:

[0027] 11: Vehicle; 12: Server;

[0028] 120: Accessibility identification system;

[0029] 121: memory; 122: processor; 123: detection device. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present invention will be described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there can be a central component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there can be a central component at the same time.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0033] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0034] An embodiment of the present invention provides a method for identifying passability. The method for identifying passability described in this embodiment can be applied to a movable platform, wherein the movable platform is provided with a detection device, and the detection device is used to detect objects around the movable platform to obtain a two-dimensional image and a three-dimensional point cloud. Optionally, the movable platform includes: a movable robot or a vehicle.

[0035] For example, the movable platform is a vehicle, which may be an unmanned vehicle or a vehicle equipped with an Advanced Driver Assistance Systems (ADAS) system. It is understandable that the method for identifying accessibility can also be applied to a movable robot, for example, a movable robot equipped with a detection device for obtaining information about its surrounding environment. Figure 1 As shown, the application scenario includes at least one vehicle 11, and the vehicle 11 is a carrier equipped with a detection device, and the detection device can specifically be a binocular stereo camera, a time of flight (TOF) camera and / or a laser radar. During the driving process of the vehicle 11, the detection device detects the surrounding environment of the vehicle 11 in real time to obtain a two-dimensional image and a three-dimensional point cloud. Among them, the binocular stereo camera and the time of flight (TOF) camera are used to collect two-dimensional images, and the laser radar is used to collect three-dimensional point clouds. It can be understood that in other embodiments, the detection device can also be a monocular camera, a millimeter wave radar, etc. This embodiment is only for exemplary description and is not limited here.

[0036] The embodiment of the present invention provides a method for identifying feasibility. Figure 2 Flow chart of the method for identifying feasibility provided by an embodiment of the present invention. Figure 2 As shown, the method in this embodiment may include:

[0037] Step S201: Set up a plurality of simulation units, each simulation unit being capable of simulating the motion of a moving object.

[0038] In this embodiment, the moving object can be Figure 1 The unmanned vehicle shown. Optionally, the execution subject of the method of this embodiment may be an unmanned driving control device, which may be a control device that performs unmanned driving control on the unmanned vehicle, specifically, a driving controller of the unmanned vehicle. This embodiment does not limit the execution subject of the passability identification method, which may be executed by a vehicle-mounted processor or by other devices with data processing functions other than the vehicle-mounted processor, for example, Figure 1 The server 12 shown, the vehicle 11 and the server 12 can perform wireless communication or wired communication, and the vehicle 11 can send the two-dimensional image and the three-dimensional point cloud to the server 12, and the server 12 executes the passability identification method. The following will take a vehicle as an example to illustrate the passability identification method provided by the embodiment of the present invention.

[0039] The simulation unit being able to simulate the movement of the moving object means that the simulation unit is able to simulate the movement of the unmanned vehicle on the ground, for example, simulating the unmanned vehicle moving on the ground in a certain direction at a certain speed and acceleration.

[0040] Optionally, the simulation unit may be a particle with random walk performance, and the particle is given the properties of a moving object so that the particle simulates the movement of the moving object.

[0041] In this embodiment, the number of simulation units can be set according to the computing power of the control device. The simulation units are dispersed in the grid map. The number of simulation units is preferably such that the entire grid map is covered to the greatest extent during the process of simulating the movement of the moving object.

[0042] Step S202, recording the access frequency of multiple simulation units to each grid in the pre-generated grid map during the process of simulating the movement of the moving object, and obtaining access frequency information; wherein the grid map is used to describe the information of the surrounding environment of the moving object.

[0043] like Figure 1As shown in the figure, the pre-generated grid map can be obtained by fusing the information collected by various detection devices on the unmanned vehicle. For example, the binocular stereo camera and the TOF camera collect the information of the environment around the unmanned vehicle to obtain a two-dimensional image, and the laser radar collects the information of the environment around the unmanned vehicle to obtain a three-dimensional point cloud. By fusing the two-dimensional image and the three-dimensional point cloud, an environmental map of the environment around the unmanned vehicle can be obtained. The grid map can be obtained by dividing the environmental map according to the pre-set grid size, and the grid map includes multiple grids. For example, according to 0.2 The environment map is divided into squares of 0.2m, resulting in a grid size of 0.2 0.2m grid map.

[0044] In a specific embodiment, the position of the unmanned vehicle in the grid map is set as the initial position of the simulation unit. In the grid map, the position of the center of the unmanned vehicle is the origin, the opposite direction of the gravity direction is the Z axis, the front of the vehicle's driving direction is the X axis, and the left of the vehicle's driving direction is the Y axis to establish a grid map coordinate system. All simulation units start from the above-set initial position and simulate the movement of the unmanned vehicle on the ground in the grid map. In the process of the simulation unit simulating the movement of the moving object, some grids in the grid map will pass through. For a grid, each time a simulation unit passes through the grid, the access frequency of the grid is increased by 1. At the end of the process of the simulation unit simulating the movement of the moving object, each grid in the grid map will correspond to an access frequency, thereby forming access frequency information. If some grids have not been visited by the simulation unit, the access frequency of the grid in the access frequency information is the initial access frequency. In one embodiment, the access frequency information can be an access frequency map. It can be understood that in other embodiments, the access frequency information can also be other suitable forms, such as an access frequency table, an access frequency value array, etc.

[0045] Step S203: Determine the accessibility of the surrounding environment of the moving object according to the access frequency information.

[0046] Specifically, through the access frequency information, we can understand the access of all simulation units to each grid in the grid map, and the access frequency of each grid is positively correlated with the size of the passability of the grid. Therefore, based on the access frequency information, the passability of the environment around the moving object, or the size of the passability, can be determined, thereby providing a basis for path planning decisions for autonomous driving.

[0047] In this embodiment, multiple simulation units are set up, each of which can simulate the movement of a moving object; the access frequency of each grid in a pre-generated grid map generated by multiple simulation units in the process of simulating the movement of the moving object is recorded to obtain access frequency information; wherein the grid map is used to describe the information of the surrounding environment of the moving object; according to the access frequency information, the passability of the surrounding environment of the moving object is determined. Since the set simulation unit can simulate the movement process of the moving object on the ground, and the simulated movement process of the simulation unit is represented by the access frequency information, the passability of the vehicle in the surrounding environment can be intuitively understood, thereby providing a basis for the decision-making of the automatic driving path planning.

[0048] Specifically, setting a plurality of simulation units includes: respectively setting the plurality of simulation units to have properties of a moving object, where the properties of the moving object include inherent properties and motion properties.

[0049] Optionally, the inherent attributes include at least size attributes. Accordingly, respectively setting multiple simulation units to have the attributes of a moving object includes at least: respectively setting multiple simulation units to have size attributes. Optionally, the size attribute means that the size of the simulation unit is not less than the size of the moving object. Accordingly, respectively setting multiple simulation units to have the attributes of a moving object includes: respectively setting the size of the multiple simulation units to be not less than the size of the moving object. In this embodiment, the size attribute of the moving object may be the width of the unmanned vehicle, that is, setting the size of the simulation unit to be not less than the width of the unmanned vehicle. Specifically, the width of the unmanned vehicle refers to the maximum distance of the unmanned vehicle in the Y direction on the grid coordinate system. As Figure 3 As shown, the size attribute can be set according to the maximum distance L between the two faces A and B relatively set on the unmanned vehicle. Of course, those skilled in the art can also set the size attribute of the simulation unit according to other reference objects on the vehicle, and this embodiment does not specifically limit this. Through this embodiment, the inherent attributes of the moving object can be given to the simulation unit. Optionally, the sizes of different simulation units can be set to different sizes, but it is necessary to ensure that the sizes of all simulation units are not less than the size of the moving object. For example, the diameter of each particle is set to be not less than the width L of the vehicle.

[0050] Optionally, the motion attribute includes at least one of an initial motion rate, an initial motion direction, an initial motion energy, a climbing ability, and a passage cost. Accordingly, setting a plurality of simulation units to have the properties of a motion object includes: setting a plurality of simulation units to have at least one of an initial motion rate, an initial motion direction, an initial motion energy, a climbing ability, and a passage cost. Through this embodiment, the motion attribute of the motion object can be given to the simulation unit, so that the simulation unit simulates the motion of the motion object. Specifically, all simulation units start from the above-set initial position and simulate the motion of the unmanned vehicle on the ground in the grid map, which means that all simulation units start from the above-set initial position and move in the grid map according to the set initial motion rate and initial motion direction. A certain amount of energy will be consumed during the motion process. When the consumed energy reaches the initial energy, the simulation unit stops simulating the motion. Climbing ability refers to the ability of the simulation unit to simulate the motion object climbing on the ground. Optionally, different simulation units can be set to different initial motion rates, initial motion directions, initial motion energies, climbing abilities, and passage costs.

[0051] This embodiment gives the simulation unit the inherent attributes and motion attributes of the autonomous driving vehicle, so that each simulation unit has a corresponding traffic capacity. The simulation unit will not reach the area beyond the traffic capacity of the simulation unit, so that the movement of the moving object can be well simulated. That is, by setting the inherent attributes and motion attributes of the simulation unit, the driving restrictions and traffic capacity of the vehicle are simulated to ensure that the simulation unit will not reach the area that the vehicle cannot reach, and finally obtain the description of the trafficability of each grid in the grid map. The trafficability of a certain area depends not only on the trafficability of the area itself, but also on the traffic cost of the vehicle to reach this place. The higher the traffic cost, the lower the trafficability of the area.

[0052] Optionally, before the simulation unit simulates the movement of the moving object, that is, in the initial state of the simulation unit, the access frequency of each grid in the pre-generated grid map is 0. Of course, the access frequency of each grid can also be set to other initial values ​​other than 0, and the present invention does not make specific limitations on this.

[0053] Correspondingly, the access frequency of each grid in the pre-generated grid map during the process of simulating the movement of the moving object by multiple simulation units is recorded to obtain the access frequency information, including: when the simulation unit takes the position of the moving object in the grid map as the initial position and presets the step length for each movement based on the motion attribute, the access frequency of the grid corresponding to the current position of the simulation unit is updated; when the number of updates reaches the preset maximum number of iterations, the access frequency information is obtained.

[0054] Optionally, when the simulation unit takes the position of the moving object in the grid map as the initial position and presets the step size for each movement based on the motion attributes, the access frequency of the grid corresponding to the current position of the simulation unit is updated, including: when the simulation unit takes the position of the moving object in the grid map as the initial position and presets the step size for each movement based on the motion attributes, marking the grid corresponding to the current position of the simulation unit on the pre-generated grid map, and adding 1 to the access frequency of the grid corresponding to the current position of the simulation unit.

[0055] In this embodiment, a preset step size is pre-set for all simulation units so that all simulation units move in the grid map according to the preset step size. Each time a simulation unit moves a preset step size, it is considered that the simulation unit has performed an iterative movement, and the access frequency of the grid corresponding to the current position of the simulation unit is updated. For example, before an iterative movement, the access frequency of a certain grid S1 is X1. After all simulation units have performed an iterative movement, X2 simulation units have moved to grid S1, and the access frequency of grid S1 is X1+X2. Among them, the preset step size refers to the displacement of the simulation unit in an iterative movement. Since each simulation unit has an initial movement speed and an initial movement direction, the movement time required for the simulation unit to perform an iterative movement can be used. To indicate the preset step length, that is, the preset step length = initial motion speed .like Figure 4 As shown, assuming that the position coordinates (e.g., the center coordinates of the particle) of the simulation unit before one iteration of motion are A0, and the position coordinates (the center coordinates of the particle) after one iteration of motion are A1, then the displacement A1A0 between the two points A0 and A1 is the preset step length. Of course, the embodiment of the present invention can also determine the preset step length according to other position coordinates of the particle, for example, the position coordinates of a point on the circumference of the particle.

[0056] Optionally, the number of updates and the number of iterations of the simulation unit may be set to be unequal, for example, the number of updates may be greater than the maximum number of iterations of the simulation unit.

[0057] Optionally, the size of the simulation unit is not less than the size of a single grid; the grid corresponding to the current position of the simulation unit refers to the grid covered by the simulation unit at the current position. Since the size of the simulation unit is not less than the size of a single grid, when the simulation unit moves to a certain grid, it will cover the grid, and each simulation unit will update its position coordinates once each iterative movement. If the updated position coordinates are within a certain grid, the grid is considered to be the grid corresponding to the current position of the simulation unit. Optionally, the position coordinates of the simulation unit can be the position coordinates of the center point of the simulation unit.

[0058] In the embodiment of the present invention, since the simulation unit has a preset size attribute, the size of the simulation unit is not less than the vehicle width. Therefore, for the connected area that the vehicle cannot pass through, the simulation unit will also be affected in the same way when moving and will not be able to pass through. This can avoid the actual inaccessible drivable area caused by the size caused by the connected domain method.

[0059] Optionally, when the simulation unit takes the position of the moving object in the grid map as the initial position and presets the step size for each movement based on the motion attributes, after updating the access frequency of the grid corresponding to the current position of the simulation unit, the method of this embodiment also includes: when the movement of the moving object meets preset conditions, updating the status information of the simulation unit, wherein the status information is represented by the travel cost.

[0060] In one embodiment, the passage cost includes a collision cost; when the movement of the moving object meets the preset conditions, the state information of the simulation unit is updated, including: when there is an obstacle grid in the grid corresponding to the current position of the simulation unit or the position coordinates of the current position of the simulation unit are the same as the position coordinates of the edge of the grid map, the movement direction of the simulation unit is updated to the rebound direction, and the collision cost of the simulation unit is calculated. Specifically, if there is an obstacle in the grid corresponding to the current position of the simulation unit or the position coordinates of the current position of the simulation unit are the same as the position coordinates of the edge of the grid map, it is considered that the simulation unit has collided, and after the collision, a collision cost will be generated. Optionally, the collision cost generated by each collision can be set to a constant. Furthermore, the single collision cost generated when there is an obstacle in the grid corresponding to the current position of the simulation unit and when the position coordinates of the current position of the simulation unit are the same as the position coordinates of the edge of the grid map can be set to different values.

[0061] Optionally, when judging whether there is an obstacle grid in the grid corresponding to the current position of the simulation unit, it can be judged by whether the local slope of the grid map is greater than the maximum climbing ability. That is, if the local slope of the grid map is greater than or equal to the maximum climbing ability, it is considered that there is an obstacle grid in the grid corresponding to the current position of the simulation unit; if the local slope of the grid map is less than the maximum climbing ability, it is considered that there is no obstacle grid in the grid corresponding to the current position of the simulation unit.

[0062] Specifically, the movement direction of the simulation unit is updated to the rebound direction, such as Figure 5 As shown in the figure, the circle represents the simulation unit, the direction indicated by the arrow V1 is the movement direction of the simulation unit before the collision, the small square at the OC point represents the impassable area, the tangent of the simulation unit at the OC position is L, and when the simulation unit collides at the OC point in the impassable area, the rebound direction is the direction indicated by the arrow of the mirror vector V2 of the movement direction V1 of the simulation unit before the collision about the tangent L.

[0063] In another embodiment, the passage cost includes a climbing cost; when the movement of the moving object meets the preset conditions, the state information of the simulation unit is updated, including: when the projection of the local slope of the grid corresponding to the current position of the simulation unit in the movement direction of the simulation unit exceeds the preset maximum slope, the movement direction of the simulation unit is updated to the rebound direction, and the collision cost of the simulation unit is calculated; when the projection of the local slope of the grid corresponding to the current position of the simulation unit in the movement direction of the simulation unit does not exceed the preset maximum slope, the climbing cost of the simulation unit is calculated, wherein the preset maximum slope can be the climbing ability set in the initial state. Optionally, the climbing cost is proportional to the local slope. Specifically, the local slope refers to the tangent value of the angle between the local normal vector of the grid map and the ground normal vector. Figure 6 As shown, it is assumed that the grid corresponding to the current position of the simulation unit is S 23 , then select grid S 23 The 4 grids or 8 grids in the neighborhood are used as the neighborhood grids. This embodiment takes the 8-grid neighborhood as an example for explanation. Assume that the grid S 23 The 8 neighborhood grids are S 12 , S 13 , S 14 , S 22 , S 24 , S 32 , S 33 , S 34 , then the grid S 23 The local slope of the grid S 12 , S 13 , S 14 , S 22 , S 24 , S 32 , S 33 , S 34 With grid S 23 The angle between the normal vector of the local fitting surface and the ground normal vector Tan The calculation of the collision cost in this embodiment can refer to the calculation process of the collision cost in the previous embodiment, and this embodiment will not be repeated here.

[0064] In the above two embodiments, calculating the collision cost of the simulation unit includes: adding a preset single collision cost to the current collision cost of the simulation unit. For example, if the current collision cost of the simulation unit is P1 and the single collision cost is P0, then after a collision occurs, the collision cost of the simulation unit is P1+P0.

[0065] In another embodiment, the travel cost includes a movement cost; when the simulation unit takes the position of the moving object in the grid map as the initial position and presets the step length for each movement based on the movement attribute, after updating the access frequency of the grid corresponding to the current position of the simulation unit, the method of the embodiment of the present invention further includes: calculating the movement mileage of the simulation unit; and calculating the movement cost based on the movement mileage. In this embodiment, Figure 7 As shown, assuming that the simulation unit moves from position a to position b and then to position c, the movement mileage of the simulation unit refers to the distance between position a and position b plus the distance between position b and position c. The movement mileage of the simulation unit is L1+L2, wherein L1 refers to the path length between position a and position b, and L2 refers to the path length between position b and position c.

[0066] Optionally, when the movement of the moving object meets the preset conditions, the state information of the simulation unit is updated, including: when the movement mileage of the simulation unit reaches the preset movement mileage, and there are no obstacles in the grids passed, the simulation unit is split into multiple sub-simulation units, and the multiple sub-simulation units continue to move along the random movement direction. For example, if the accumulated movement mileage of a simulation unit reaches the preset movement mileage, and before that, the simulation unit has passed through N grids, and there are no obstacles in these N grids or the simulation unit has not collided during the movement, then the area corresponding to these N grids is considered to be an open area. By splitting the simulation unit into multiple sub-simulation units and allowing the multiple sub-simulation units to continue to move along the random movement direction, the search efficiency of the open area can be accelerated and the coverage of the open area can be improved.

[0067] Optionally, when the movement of the moving object meets preset conditions, the state information of the simulation unit is updated, including: calculating the cumulative travel cost of the simulation unit; when the cumulative travel cost of the simulation unit exceeds the initial energy, the simulation unit stops moving.

[0068] Optionally, calculating the cumulative travel cost of the simulation unit includes: when the simulation unit presets a step length for each movement based on the movement attribute, calculating the travel cost of the simulation unit; and accumulating the travel costs of all movements from the current movement forward to obtain the cumulative travel cost. The travel cost includes at least one of a collision cost, a climbing cost, and a movement cost.

[0069] In this embodiment, if the passage cost includes collision cost, climbing cost and movement cost, the cumulative passage cost refers to the cumulative value of the cumulative collision cost, the cumulative climbing cost and the cumulative movement cost, and the cumulative collision cost, the cumulative climbing cost and the cumulative movement cost are recorded as , , ; Assuming that the simulation unit moves iteratively M times, the cumulative travel cost of M times is ; If the cumulative cost of M trips When the initial energy is exceeded, it is considered that the initial energy of the simulation unit has been consumed and it will no longer participate in subsequent iterative movements.

[0070] The embodiment of the present invention explores the area in the grid map by using random movement of particles. Particles with random movement direction and speed start from the location of the vehicle. The terrain features in the grid map (obstacle collision, slope, and particle travel distance) will impose a certain travel cost on the particles. Each particle has a certain initial energy to resist the external travel cost.

[0071] For a single particle, if the cost of reaching a certain area is high, it is possible that the set initial energy is exhausted before reaching the area and it cannot reach the area. From the access frequency information, the number of particles that can reach the area is smaller. Conversely, for areas with lower cost, more particles can reach the area. Finally, the frequency of particles passing through a certain area is used to calculate the passability of the area.

[0072] Optionally, the accessibility of the surrounding environment of the moving object is determined based on the access frequency information, including: marking the accessibility and / or accessibility probability of the grid in the access frequency information.

[0073] Optionally, in the access frequency information, the passability and / or passability probability of the marking grid includes: marking the grid whose access frequency in the access frequency information is greater than the first preset access frequency as passable, and / or marking the passability probability as greater than the first preset probability threshold; marking the grid whose access frequency in the access frequency information is less than the second preset access frequency as inaccessible, and / or the passability probability is less than the second preset probability threshold; marking the grid whose access frequency in the access frequency information is greater than or equal to the second preset access frequency and less than or equal to the first preset access frequency as passable and / or the calculated passability probability, wherein the first preset probability threshold can be set to less than 100%, for example, greater than or equal to 50% and less than 100%; the second preset threshold can be set to greater than 0, for example, greater than 0 and less than 10%, and the first preset probability threshold is greater than the second preset probability threshold. If the pass probability is greater than the first preset probability threshold, the grid is considered passable, and the maximum pass probability can reach 100%; if the pass probability is less than the second preset probability threshold, the grid is considered impassable, and the minimum impassable pass probability can reach 0. Optionally, the grid whose pass probability is greater than or equal to the second preset probability threshold and less than or equal to the first preset probability threshold can be marked as possibly passable. A specific pass probability can be given for the grid that is possibly passable.

[0074] Optionally, the pass probability is calculated based on the access frequency of the grid, the first preset access frequency, and the second preset access frequency. Specifically, it can be calculated according to the following formula:

[0075] (1)

[0076] In formula (1), is the passing probability; is the access frequency of the grid after the update is completed; is the second preset access frequency, is the first preset access frequency.

[0077] Of course, in the embodiment of the present invention, a probability threshold may be set to mark grids with a probability greater than or equal to the probability threshold as passable, and grids with a probability less than the probability threshold as impassable.

[0078] Figure 8 FIG. 1 is a flow chart of another method for identifying feasibility provided by an embodiment of the present invention. Figure 8 As shown, before recording the access frequency of each grid in the pre-generated grid map during the process of simulating the motion of the moving object by multiple simulation units and obtaining the access frequency information, the method of the embodiment of the present invention further includes the following steps:

[0079] Step S801, obtaining a 2.5D grid map.

[0080] like Figure 1 As shown in the figure, a 2.5D grid map describing the environment around the autonomous vehicle can be obtained by fusing the two-dimensional image and three-dimensional point cloud collected by the detection equipment on the vehicle. The length and width directions of the 2.5D grid map describe the horizontal plane with grids of equal resolution, and the height within the grid is the maximum height value of the corresponding position of the grid. The corresponding position of the grid refers to the grid corresponding to the actual position with the autonomous vehicle as the origin. The grid position coordinates are recorded as ,

[0081] (2)

[0082] In formula (2), is the resolution of the 2.5D grid map in the length direction; The position coordinate of the vehicle's surrounding environment information on the x-axis in the vehicle coordinate system, in physical length, which can be in meters; Express Rounding;

[0083] (3)

[0084] In formula (3), is the resolution of the 2.5D grid map in the width direction; The position coordinate of the vehicle's surrounding environment information on the y-axis in the vehicle coordinate system, in physical length, which can be in meters; Express Round up.

[0085] Step S802: For each grid in the 2.5D grid map, calculate the grid height of the grid and the corresponding neighboring grids.

[0086] Specifically, for each grid in the 2.5D grid map, the grid height of the grid and the corresponding four neighboring grids, or the grid height of the eight neighboring grids, can be calculated. The grid height refers to the height of the grid relative to the ground, that is, the height relative to the ground.

[0087] Step S803: determining characteristic information of the grid based on the grid heights of the grid and the corresponding neighborhood grids, wherein the characteristic information includes at least a maximum grid height, a minimum grid height, an average grid height, and a local slope.

[0088] Specifically, the maximum grid height, the minimum grid height, the average grid height and the local slope are determined among the grid heights of four neighborhood grids or eight neighborhood grids, and are bound to the grid as feature information of the grid.

[0089] Step S804: determine whether the grid is a passable grid based on the feature information, and obtain a grid map.

[0090] Specifically, whether the grid is a passable grid can be determined by judging whether the height difference between the maximum grid height and the minimum grid height is less than the passable threshold, whether the variance of the local height value is less than the passable threshold, and whether the local slope is less than at least one of the climbing ability, thereby obtaining the grid map of the above embodiment. On the basis of this grid map, the access frequency information can be further obtained.

[0091] The following is an explanation of the beneficial effects of the embodiments of the present invention by comparing experimental data:

[0092] Fig. 9 This is a diagram of feasibility recognition results in the prior art.

[0093] Fig.10 The access frequency information is obtained by using the method of the embodiment of the present invention, wherein the access frequency information is in the form of an access frequency graph.

[0094] Fig.11 This is a feasibility recognition result diagram obtained by using the method of an embodiment of the present invention.

[0095] Fig. 9, Fig.10 and Fig.11 It is to identify the accessibility of the same environment. Fig. 9 As shown in the figure, the gray area represents the identified passable area. It can be seen that the narrow strip area R in the left box in the figure is identified as a passable area, but because the width of the autonomous driving vehicle is larger than the narrow strip area, the autonomous driving vehicle still cannot pass through. Therefore, this part of area R is actually an impassable area. The wider area W in the right box in the figure is wider than the width of the vehicle, but the area below W is narrower. Therefore, the vehicle cannot actually reach the W area, and the W area is actually an impassable area.

[0096] like Fig.10 , Fig.11 As shown in the figure, the lighter color area is the identified passable area. The lighter the color, the higher the passability. Conversely, the darker the color, the lower the passability. Fig.10 , Fig.11 As can be seen in Fig. 9 The grids corresponding to the R area and the W area in the simulation unit will not be accessed. Therefore, the method of the embodiment of the present invention can improve the recognition accuracy of feasibility.

[0097] The embodiment of the present invention provides a system for identifying accessibility. Fig.12 The structure diagram of the feasibility identification system provided by the embodiment of the present invention is as follows: Fig.12 As shown, the accessibility identification system 120 includes: a memory 121, a processor 122 and a detection device 123; the detection device is used to detect the surrounding environment information of the movable platform to obtain a two-dimensional image and a three-dimensional point cloud; the memory 121 is used to store program code; the processor 122 calls the program code, and when the program code is executed, it is used to perform the following operations: obtain a grid map based on the fusion of the two-dimensional image and the three-dimensional point cloud; set up multiple simulation units, each of which can simulate the movement of a moving object; record the access frequency of each grid in the pre-generated grid map during the process of simulating the movement of the moving object by multiple simulation units to obtain access frequency information; wherein, the grid map is used to describe the information of the surrounding environment of the moving object; and determine the accessibility of the surrounding environment of the moving object according to the access frequency information.

[0098] Optionally, when setting a plurality of simulation units, the processor 122 is specifically configured to: respectively set the plurality of simulation units to have properties of the motion object, where the properties of the motion object include inherent properties and motion properties.

[0099] Optionally, the inherent attributes at least include a size attribute; when the processor 122 separately sets the multiple simulation units to have the attributes of the moving object, it is at least used to: separately set the multiple simulation units to have the size attribute.

[0100] Optionally, the size attribute means that the size of the simulation unit is not less than the size of the moving object; when the processor 122 sets the multiple simulation units to have the attributes of the moving object respectively, it is specifically used to: set the sizes of the multiple simulation units to be not less than the size of the moving object respectively.

[0101] Optionally, the motion attributes include at least one of an initial motion rate, an initial motion direction, an initial motion energy, a climbing ability and a passing cost; when the processor 122 separately sets the multiple simulation units to have the attributes of the moving object, it is specifically used to: separately set the multiple simulation units to have at least one of the initial motion rate, the initial motion direction, the initial motion energy, the climbing ability and the passing cost.

[0102] Optionally, before the simulation unit simulates the movement of the moving object, the access frequency of each grid in the pre-generated grid map is 0; when the processor 122 obtains the access frequency information by recording the access frequency of each grid in the pre-generated grid map in the process of simulating the movement of the moving object by multiple simulation units, it is specifically used to: when the simulation unit takes the position of the moving object in the grid map as the initial position and presets a step size for each movement based on the motion attribute, update the access frequency of the grid corresponding to the current position of the simulation unit; when the number of updates reaches the preset maximum number of iterations, obtain the access frequency information.

[0103] Optionally, when the simulation unit takes the position of the moving object in the grid map as the initial position and presets a step size for each movement based on the motion attribute, the processor 122 updates the access frequency of the grid corresponding to the current position of the simulation unit. Specifically, when the simulation unit takes the position of the moving object in the grid map as the initial position and presets a step size for each movement based on the motion attribute, the grid corresponding to the current position of the simulation unit is marked on the pre-generated grid map, and the access frequency of the grid corresponding to the current position of the simulation unit is increased by 1.

[0104] Optionally, the size of the simulation unit is not smaller than the size of a single grid; the grid corresponding to the current position of the simulation unit refers to the grid covered by the simulation unit at the current position.

[0105] Optionally, after the simulation unit takes the position of the moving object in the grid map as the initial position and updates the access frequency of the grid corresponding to the current position of the simulation unit based on the preset step size of each movement of the motion attribute, the processor 122 is also used to: when the movement of the moving object meets preset conditions, update the status information of the simulation unit, and the status information is represented by the pass cost.

[0106] Optionally, the passage cost includes a collision cost; when the processor 122 updates the status information of the simulation unit when the movement of the moving object meets a preset condition, it is specifically used to: when there is an obstacle grid in the grid corresponding to the current position of the simulation unit or the position coordinates of the current position of the simulation unit are the same as the position coordinates of the edge of the grid map, update the movement direction of the simulation unit to the rebound direction, and calculate the collision cost of the simulation unit.

[0107] Optionally, the passage cost includes a climbing cost; when the processor 122 updates the status information of the simulation unit when the movement of the moving object meets a preset condition, it is specifically used to: when the projection of the local slope of the grid corresponding to the current position of the simulation unit on the movement direction of the simulation unit exceeds a preset maximum slope, the movement direction of the simulation unit is updated to a rebound direction, and the collision cost of the simulation unit is calculated; when the projection of the local slope of the grid corresponding to the current position of the simulation unit on the movement direction of the simulation unit does not exceed the preset maximum slope, the climbing cost of the simulation unit is calculated.

[0108] Optionally, when calculating the collision cost of the simulation unit, the processor 122 is specifically configured to: add a preset single collision cost on the basis of the current collision cost of the simulation unit.

[0109] Optionally, the climbing cost is proportional to the slope.

[0110] Optionally, the travel cost includes a motion cost; after the processor 122 updates the access frequency of the grid corresponding to the current position of the simulation unit when the simulation unit takes the position of the moving object in the grid map as the initial position and presets a step size for each movement based on the motion attribute, it is also used to: calculate the movement mileage of the simulation unit; and calculate the motion cost based on the movement mileage.

[0111] Optionally, when the movement of the moving object satisfies a preset condition, the processor 122 updates the status information of the simulation unit, and is specifically used to: when the movement mileage of the simulation unit reaches a preset movement mileage and there are no obstacle grids in the marked grids, split the simulation unit into multiple sub-simulation units, and make the multiple sub-simulation units continue to move along a random movement direction.

[0112] Optionally, when the movement of the moving object meets a preset condition, the processor 122 updates the state information of the simulation unit, and is specifically used to: calculate the cumulative pass cost of the simulation unit; when the cumulative pass cost of the simulation unit exceeds the initial energy, the simulation unit stops moving.

[0113] Optionally, when calculating the cumulative pass cost of the simulation unit, the processor 122 is specifically used to: when the simulation unit presets a step size for each movement based on the movement attribute, calculate the pass cost of the simulation unit; from the current movement forward, add up the pass costs of all movements to obtain the cumulative pass cost.

[0114] Optionally, the passage cost includes at least one of a collision cost, a climbing cost and a movement cost.

[0115] Optionally, when determining the passability of the surrounding environment of the moving object according to the access frequency information, the processor 122 is specifically configured to: mark the passability and / or passability probability of the grid in the access frequency information.

[0116] Optionally, when the processor 122 marks the passability and / or passability probability of the grid in the access frequency information, it is specifically used to: mark the grid in the access frequency information whose access frequency is greater than a first preset access frequency as passable, and / or mark the passability probability as greater than a first preset probability threshold; mark the grid in the access frequency information whose access frequency is less than a second preset access frequency as inaccessible, and / or the passability probability is less than a second preset probability threshold; mark the grid in the access frequency information whose access frequency is greater than or equal to the second preset access frequency and less than or equal to the first preset access frequency as passable and / or the calculated passability probability, wherein the first preset probability threshold is greater than the second preset probability threshold.

[0117] Optionally, the passage probability is calculated based on the access frequency of the grid, the first preset access frequency, and the second preset access frequency.

[0118] Optionally, the moving object is a movable robot or a vehicle. Specifically, the vehicle may be an unmanned vehicle or a vehicle equipped with an ADAS system, etc.

[0119] Optionally, the simulation unit is a particle with random walk performance.

[0120] Optionally, before recording the access frequency of each grid in the pre-generated grid map when multiple simulation units simulate the movement of the moving object and obtaining the access frequency information, the processor 122 is also used to: obtain a 2.5D grid map; for each grid in the 2.5D grid map, calculate the grid height of the grid and the corresponding neighborhood grids; based on the grid heights of the grid and the corresponding neighborhood grids, determine feature information of the grid, the feature information including at least the maximum grid height, the minimum grid height, the average grid height, and the local slope; based on the feature information, determine whether the grid is a passable grid to obtain the pre-generated grid map.

[0121] The specific principles and implementation methods of the feasibility identification system provided in the embodiment of the present invention are similar to those in the above embodiment and will not be described in detail here.

[0122] In this embodiment, multiple simulation units are set up, each of which can simulate the movement of a moving object; the access frequency of each grid in a pre-generated grid map generated by multiple simulation units in the process of simulating the movement of the moving object is recorded to obtain access frequency information; wherein the grid map is used to describe the information of the surrounding environment of the moving object; according to the access frequency information, the passability of the surrounding environment of the moving object is determined. Since the set simulation unit can simulate the movement process of the moving object on the ground, and the simulated movement process of the simulation unit is represented by the access frequency information, the passability of the vehicle in the surrounding environment can be intuitively understood, thereby providing a basis for the decision-making of the automatic driving path planning.

[0123] An embodiment of the present invention provides a movable platform. The movable platform includes: a fuselage, a power system and the passability identification system described in the above embodiment; wherein the power system is installed on the fuselage to provide power for movement. The specific implementation method and principle of the passability identification system are consistent with the above embodiment and will not be repeated here. Optionally, the movable platform includes: a movable robot or a vehicle. When the movable platform is a vehicle, the fuselage may include the body, chassis and other load-bearing parts of the vehicle. When the passability identification system is a separate device, it can be integrated into the movable platform such as a vehicle in a pre-installed or post-installed form; when the passability identification system is a distributed system, its various parts such as detection equipment, processors and memories can be installed in the same or different positions on the movable platform.

[0124] In addition, this embodiment further provides a computer-readable storage medium on which a computer program is stored. The computer program is executed by a processor to implement the method for identifying accessibility described in the above embodiment.

[0125] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0126] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0127] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0128] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0129] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying accessibility, characterized in that: include: Setting a plurality of simulation units, each of which can simulate the motion of a moving object, wherein the size of the simulation unit is not less than the size of the moving object; Recording the access frequency of each grid in the pre-generated grid map by the plurality of simulation units in the process of simulating the movement of the moving object, and obtaining access frequency information; wherein the grid map is used to describe the information of the surrounding environment of the moving object; The accessibility of the surrounding environment of the moving object is determined according to the access frequency information, and the access frequency of each grid is positively correlated with the size of the accessibility of the grid.

2. The method according to claim 1, characterized in that The multiple simulation units are provided, including: The plurality of simulation units are respectively configured to have properties of the moving object, and the properties of the moving object include inherent properties and motion properties.

3. The method according to claim 2, characterized in that The inherent properties include at least size properties; The respectively setting of the plurality of simulation units to have the attributes of the moving object comprises at least: The plurality of simulation units are respectively set to have the size attribute.

4. The method according to claim 3, characterized in that The size attribute means that the size of the simulation unit is not less than the size of the moving object; The respectively setting of the plurality of simulation units to have the attributes of the moving object comprises: The sizes of the plurality of simulation units are respectively set to be no smaller than the size of the moving object.

5. The method according to claim 2, characterized in that: The motion attribute includes at least one of an initial motion rate, an initial motion direction, an initial motion energy, a gradeability, and a travel cost; The respectively setting of the plurality of simulation units to have the attributes of the moving object comprises: The plurality of simulation units are respectively configured to have at least one of the initial movement rate, the initial movement direction, the initial movement energy, the gradeability and the travel cost.

6. The method according to claim 5, characterized in that Before the plurality of simulation units simulate the movement of the moving object, the access frequency of each grid in the pre-generated grid map is 0; The recording of the access frequency of each grid in the pre-generated grid map during the process of simulating the movement of the moving object by the plurality of simulation units to obtain the access frequency information includes: When the simulation unit takes the position of the moving object in the grid map as the initial position and presets a step length for each movement based on the motion attribute, the access frequency of the grid corresponding to the current position of the simulation unit is updated; When the number of updates reaches a preset maximum number of iterations, the access frequency information is obtained.

7. The method according to claim 6, characterized in that When the simulation unit takes the position of the moving object in the grid map as the initial position and presets a step length for each movement based on the motion attribute, updating the access frequency of the grid corresponding to the current position of the simulation unit includes: When the simulation unit takes the position of the moving object in the grid map as the initial position and presets the step size for each movement based on the motion attribute, the grid corresponding to the current position of the simulation unit is marked on the pre-generated grid map, and the access frequency of the grid corresponding to the current position of the simulation unit is increased by 1.

8. The method according to claim 7, characterized in that The size of the simulation unit is not less than the size of a single grid; The grid corresponding to the current position of the simulation unit refers to the grid covered by the simulation unit at the current position.

9. The method according to claim 7, characterized in that: After the simulation unit takes the position of the moving object in the grid map as the initial position and presets a step length for each movement based on the motion attribute, and updates the access frequency of the grid corresponding to the current position of the simulation unit, the method further includes: When the movement of the moving object meets a preset condition, the state information of the simulation unit is updated, and the state information is represented by the travel cost.

10. The method according to claim 9, characterized in that The passage cost includes collision cost; When the motion of the moving object satisfies a preset condition, updating the state information of the simulation unit comprises: When there is an obstacle grid in the grid corresponding to the current position of the simulation unit or the position coordinates of the current position of the simulation unit are the same as the position coordinates of the edge of the grid map, the movement direction of the simulation unit is updated to the rebound direction, and the collision cost of the simulation unit is calculated.

11. The method according to claim 9, characterized in that The passage cost includes the climbing cost; When the motion of the moving object satisfies a preset condition, updating the state information of the simulation unit comprises: When the projection of the local slope of the grid corresponding to the current position of the simulation unit on the movement direction of the simulation unit exceeds a preset maximum slope, the movement direction of the simulation unit is updated to a rebound direction, and the collision cost of the simulation unit is calculated; When the projection of the local slope of the grid corresponding to the current position of the simulation unit in the moving direction of the simulation unit does not exceed the preset maximum slope, the climbing cost of the simulation unit is calculated.

12. The method according to claim 10 or 11, characterized in that: The calculating the collision cost of the simulation unit includes: A preset single collision cost is added on the basis of the current collision cost of the simulation unit.

13. The method according to claim 11, characterized in that The climbing cost is proportional to the local slope.

14. The method according to claim 9, characterized in that The passage cost includes movement cost; After the simulation unit takes the position of the moving object in the grid map as the initial position and presets a step length for each movement based on the motion attribute, and updates the access frequency of the grid corresponding to the current position of the simulation unit, the method further includes: Calculating the movement mileage of the simulation unit; An exercise cost is calculated based on the exercise mileage.

15. The method according to claim 14, characterized in that When the motion of the moving object satisfies a preset condition, updating the state information of the simulation unit comprises: When the movement mileage of the simulation unit reaches a preset movement mileage and there are no obstacle grids in the passed grids, the simulation unit is split into multiple sub-simulation units, and the multiple sub-simulation units continue to move along the random movement direction.

16. The method according to claim 9, characterized in that When the motion of the moving object satisfies a preset condition, updating the state information of the simulation unit comprises: Calculating the accumulated travel cost of the simulation unit; When the accumulated travel cost of the simulation unit exceeds the initial energy, the simulation unit stops moving.

17. The method according to claim 16, characterized in that The calculating the accumulated travel cost of the simulation unit includes: When the simulation unit presets a step length per movement based on the movement attribute, the travel cost of the simulation unit is calculated; From the current movement onward, the travel costs of all movements are accumulated to obtain the accumulated travel cost.

18. The method according to claim 5 or 9, characterized in that: The passage cost includes at least one of a collision cost, a climbing cost and a movement cost.

19. The method according to claim 1, characterized in that The determining, according to the access frequency information, the accessibility of the surrounding environment of the moving object comprises: The accessibility and / or accessibility probability of the grid are marked according to the access frequency information.

20. The method according to claim 19, characterized in that The step of marking the accessibility and / or accessibility probability of the grid according to the access frequency information comprises: Marking the grids in the access frequency information whose access frequency is greater than the first preset access frequency as passable, and / or marking the pass probability as greater than the first preset probability threshold; Marking the grids in the access frequency information whose access frequency is less than the second preset access frequency as inaccessible, and / or whose access probability is less than the second preset probability threshold; The grids in the access frequency information whose access frequency is greater than or equal to the second preset access frequency and less than or equal to the first preset access frequency are marked as passable and / or the pass probability is calculated, wherein the first preset probability threshold is greater than the second preset probability threshold.

21. The method according to claim 20, characterized in that The pass probability is calculated according to the access frequency of the grid, the first preset access frequency, and the second preset access frequency.

22. The method according to any one of claims 1 to 5, characterized in that: The moving object is a movable robot or a vehicle.

23. The method according to any one of claims 1 to 5, characterized in that: The simulation unit is a particle with random walk performance.

24. The method according to any one of claims 1 to 5, characterized in that: Before recording the access frequency of each grid in the pre-generated grid map during the process of simulating the movement of the moving object by the plurality of simulation units and obtaining the access frequency information, the method further comprises: Get 2.5D grid map; For each grid in the 2.5D grid map, calculating the grid height of the grid and the corresponding neighboring grids; Determine characteristic information of the grid based on the grid heights of the grid and the corresponding neighborhood grids, wherein the characteristic information includes at least a maximum grid height, a minimum grid height, an average grid height, and a local slope; Based on the feature information, it is determined whether the grid is a passable grid, and a grid map is obtained.

25. The method according to any one of claims 1 to 5, characterized in that: The access frequency information includes an access frequency map.

26. A system for identifying accessibility, characterized in that: include: Probe devices, memory, and processors; The detection device is used to detect the surrounding environment information of the movable platform to obtain a two-dimensional image and a three-dimensional point cloud; The memory is used to store program code; The processor calls the program code, and when the program code is executed, is used to perform the following operations: Setting a plurality of simulation units, each of which can simulate the motion of a moving object, wherein the size of the simulation unit is not less than the size of the moving object; Recording the access frequency of each grid in the pre-generated grid map during the process of simulating the movement of the moving object by the plurality of simulation units, and obtaining access frequency information; wherein the grid map is used to describe the information of the surrounding environment of the moving object; the pre-generated grid map is obtained by fusing the two-dimensional image and the three-dimensional point cloud; The accessibility of the surrounding environment of the moving object is determined according to the access frequency information, and the access frequency of each grid is positively correlated with the size of the accessibility of the grid.

27. The system according to claim 26, characterized in that When the processor sets a plurality of simulation units, it is specifically used to: The plurality of simulation units are respectively configured to have properties of the moving object, and the properties of the moving object include inherent properties and motion properties.

28. The system according to claim 27, characterized in that The inherent properties include at least size properties; When the processor respectively sets the plurality of simulation units to have the attributes of the moving object, the processor is at least used to: The plurality of simulation units are respectively set to have the size attribute.

29. The system according to claim 28, characterized in that The size attribute means that the size of the simulation unit is not less than the size of the moving object; When the processor respectively sets the plurality of simulation units to have the attributes of the moving object, the processor is specifically configured to: The sizes of the plurality of simulation units are respectively set to be no smaller than the size of the moving object.

30. The system according to claim 27, characterized in that The motion attribute includes at least one of an initial motion rate, an initial motion direction, an initial motion energy, a gradeability, and a travel cost; When the processor respectively sets the plurality of simulation units to have the attributes of the moving object, the processor is specifically configured to: The plurality of simulation units are respectively configured to have at least one of the initial movement rate, the initial movement direction, the initial movement energy, the gradeability and the travel cost.

31. The system according to claim 30, characterized in that Before the simulation unit simulates the movement of the moving object, the access frequency of each of the grids in the pre-generated grid map is 0; When the processor records the access frequency of each grid in the pre-generated grid map during the process of simulating the movement of the moving object by the plurality of simulation units to obtain the access frequency information, it is specifically used to: When the simulation unit takes the position of the moving object in the grid map as the initial position and presets a step length for each movement based on the motion attribute, updating the access frequency of the grid corresponding to the current position of the simulation unit; When the number of updates reaches a preset maximum number of iterations, the access frequency information is obtained.

32. The system according to claim 31, characterized in that When the simulation unit takes the position of the moving object in the grid map as the initial position and presets a step length per movement based on the motion attribute, the processor updates the access frequency of the grid corresponding to the current position of the simulation unit, specifically for: When the simulation unit takes the position of the moving object in the grid map as the initial position and presets the step size for each movement based on the motion attribute, the grid corresponding to the current position of the simulation unit is marked on the pre-generated grid map, and the access frequency of the grid corresponding to the current position of the simulation unit is increased by 1.

33. The system according to claim 32, characterized in that The size of the simulation unit is not less than the size of a single grid; The grid corresponding to the current position of the simulation unit refers to the grid covered by the simulation unit at the current position.

34. The system according to claim 32, characterized in that The processor is further configured to: after the simulation unit updates the access frequency of the grid corresponding to the current position of the simulation unit when the simulation unit takes the position of the moving object in the grid map as the initial position and presets the step length for each movement based on the motion attribute: When the movement of the moving object meets a preset condition, the state information of the simulation unit is updated, and the state information is represented by the travel cost.

35. The system according to claim 34, characterized in that The passage cost includes collision cost; When the motion of the moving object satisfies a preset condition, the processor updates the state information of the simulation unit, specifically for: When there is an obstacle grid in the grid corresponding to the current position of the simulation unit or the position coordinates of the current position of the simulation unit are the same as the position coordinates of the edge of the grid map, the movement direction of the simulation unit is updated to the rebound direction, and the collision cost of the simulation unit is calculated.

36. The system according to claim 34, characterized in that The passage cost includes the climbing cost; When the motion of the moving object satisfies a preset condition, the processor updates the state information of the simulation unit, specifically for: When the projection of the local slope of the grid corresponding to the current position of the simulation unit on the movement direction of the simulation unit exceeds a preset maximum slope, the movement direction of the simulation unit is updated to a rebound direction, and the collision cost of the simulation unit is calculated; When the projection of the local slope of the grid corresponding to the current position of the simulation unit in the moving direction of the simulation unit does not exceed the preset maximum slope, the climbing cost of the simulation unit is calculated.

37. The system according to claim 35 or 36, characterized in that When calculating the collision cost of the simulation unit, the processor is specifically used to: A preset single collision cost is added on the basis of the current collision cost of the simulation unit.

38. The system according to claim 36, characterized in that The climbing cost is proportional to the local slope.

39. The system according to claim 34, characterized in that The passage cost includes movement cost; The processor is further configured to: after the simulation unit updates the access frequency of the grid corresponding to the current position of the simulation unit when the simulation unit takes the position of the moving object in the grid map as the initial position and presets the step length for each movement based on the motion attribute: Calculating the movement mileage of the simulation unit; An exercise cost is calculated based on the exercise mileage.

40. The system according to claim 39, characterized in that When the motion of the moving object satisfies a preset condition, the processor updates the state information of the simulation unit, specifically for: When the movement mileage of the simulation unit reaches a preset movement mileage and there are no obstacle grids in the marked grids, the simulation unit is split into multiple sub-simulation units, and the multiple sub-simulation units continue to move along random movement directions.

41. The system of claim 34, wherein: When the motion of the moving object satisfies a preset condition, the processor updates the state information of the simulation unit, specifically for: Calculating the accumulated travel cost of the simulation unit; When the accumulated travel cost of the simulation unit exceeds the initial energy, the simulation unit stops moving.

42. The system according to claim 41, characterized in that When calculating the accumulated travel cost of the simulation unit, the processor is specifically used to: When the simulation unit presets a step length per movement based on the movement attribute, the travel cost of the simulation unit is calculated; From the current movement onward, the travel costs of all movements are accumulated to obtain the accumulated travel cost.

43. The system according to claim 30 or 34, characterized in that The passage cost includes at least one of a collision cost, a climbing cost and a movement cost.

44. The system according to claim 26, characterized in that When the processor determines the passability of the surrounding environment of the moving object according to the access frequency information, it is specifically used to: The accessibility and / or accessibility probability of the grid are marked according to the access frequency information.

45. The system according to claim 44, characterized in that When the processor marks the accessibility and / or accessibility probability of the grid according to the access frequency information, it is specifically used to: Marking the grids in the access frequency information whose access frequency is greater than the first preset access frequency as passable, and / or marking the pass probability as greater than the first preset probability threshold; Marking the grids in the access frequency information whose access frequency is less than the second preset access frequency as inaccessible, and / or whose access probability is less than the second preset probability threshold; The grids in the access frequency information whose access frequency is greater than or equal to the second preset access frequency and less than or equal to the first preset access frequency are marked as passable and / or the pass probability is calculated, wherein the first preset probability threshold is greater than the second preset probability threshold.

46. ​​The system according to claim 45, characterized in that The pass probability is calculated according to the access frequency of the grid, the first preset access frequency, and the second preset access frequency.

47. The system according to any one of claims 26 to 30, characterized in that: The moving object is a movable robot or a vehicle.

48. The system according to any one of claims 26 to 30, characterized in that: The simulation unit is a particle with random walk performance.

49. The system according to any one of claims 26 to 30, characterized in that: The processor is further used, before recording the access frequency of each grid in the pre-generated grid map during the process of simulating the motion of the moving object by the plurality of simulation units, and obtaining the access frequency information: Get 2.5D grid map; For each grid in the 2.5D grid map, calculating the grid height of the grid and the corresponding neighboring grids; Determine characteristic information of the grid based on the grid heights of the grid and the corresponding neighborhood grids, wherein the characteristic information includes at least a maximum grid height, a minimum grid height, an average grid height, and a local slope; Based on the feature information, it is determined whether the grid is a passable grid, and the pre-generated grid map is obtained.

50. The system according to any one of claims 26 to 30, characterized in that: The access frequency information includes an access frequency map.

51. A movable platform, characterized in that: include: body; A power system, installed on the fuselage, for providing movement power; And the system described in any one of claims 26-50.

52. The movable platform according to claim 51, characterized in that: The movable platform includes: a movable robot or a vehicle.

53. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 25.

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