CN115420287A - Path planning method, device, electronic device and storage medium - Google Patents

Abstract

The invention provides a path planning method, a path planning device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring global environment information corresponding to an unknown environment, and determining a current path corresponding to an initial position and a terminal position according to the global environment information; segmenting the current path to obtain a plurality of segmented paths, and sampling the segmented paths to obtain a plurality of path points; under the condition that the unmanned aerial vehicle is determined to collide with a target segmented path corresponding to the target path point, updating global environment information by using local environment information corresponding to the target segmented path acquired by a vision sensor to obtain new global environment information; and determining a target path corresponding to the starting position and the end position by utilizing an A-x algorithm based on the new global environment information. The method is used for achieving that the electronic equipment can obtain the target path of the unmanned aerial vehicle between the starting position and the end position under the condition that the unmanned aerial vehicle is in an unknown environment, the planning time of the target path is short, and the target path is a better path.

Description

Path planning method, device, electronic device and storage medium

technical field

The present invention relates to the technical field of path planning, in particular to a path planning method, device, electronic equipment and storage medium.

Background technique

With the development of science and technology, the application of drones is becoming more and more extensive.

The existing path planning method for UAVs is as follows: the electronic device can use the traditional A* algorithm to plan the path of the UAV flying from the starting position to the terminal position. The traditional A* algorithm is a graph search algorithm, which is an effective direct search method for solving the shortest path in a statically known environment, and is also based on the Dijkstra algorithm and the breadth-first search algorithm. Heuristic search algorithm. In the process of path search, that is, path planning, the electronic device can use the cost function in the traditional A* algorithm to evaluate the feasibility of the path point between the starting position and the final position, and select the node with the smallest cost value as the next step The expanded node then continues from the next node until reaching the end position, which results in more time for the entire path planning and more meshes to be traversed. In addition, the traditional A* algorithm can only be applied to the autonomous navigation of UAVs when the global environment is known, which has certain limitations.

In this way, although the electronic device can find the flight path between the starting position and the end position for the UAV, due to the long planning search time of the flight path and the limitation of the path planning method used, the , the flight path obtained by the electronic device is not an optimal path between the starting location and the ending location.

Contents of the invention

The present invention provides a path planning method, device, electronic equipment and storage medium to solve the problem that although the electronic equipment in the prior art can find the flight path between the start position and the end position of the drone, due to the The path planning search time is relatively long and the path planning method used has certain limitations, resulting in the defect that the flight path obtained by the electronic device is not the optimal path between the starting position and the end position. When the UAV is in an unknown environment, the current path executed by the UAV is segmented, and the A* algorithm is used to obtain the target path between the starting position and the end position of the UAV. The planning time of the path is shorter, and it is a better path.

The present invention provides a path planning method, including:

Obtain the global environment information corresponding to the unknown environment, and determine the current path corresponding to the start position and the end position according to the global environment information;

Segmenting the current path to obtain multiple segmented paths, and sampling the multiple segmented paths to obtain multiple path points;

When it is determined that the UAV collides with the target segment path corresponding to the target way point, the local environment information corresponding to the target segment path acquired by the visual sensor is used to update the global environment information to obtain new global environment information. The target waypoint is any one of the plurality of waypoints;

Based on the new global environment information, the A* algorithm is used to determine the target path corresponding to the start position and the end position.

According to a path planning method provided by the present invention, determining the current path corresponding to the start position and the end position according to the global environment information includes: determining the start position and the end position from the global environment information; The starting position and the end position are connected to obtain a straight line path.

According to a path planning method provided by the present invention, the current path is segmented to obtain multiple segmented paths, and the multiple segmented paths are sampled to obtain multiple path points, including: In the process of executing the straight-line path, the straight-line path is segmented using the length of the visual cone corresponding to the visual sensor to obtain a plurality of segmented paths, and the visual sensor is set on the UAV; Discretize sampling to get multiple path points.

According to a path planning method provided by the present invention, performing discretization sampling on the plurality of segmented routes to obtain a plurality of route points includes: performing discrete sampling on the plurality of segmented routes according to a preset map resolution , to get multiple waypoints.

According to a path planning method provided by the present invention, performing discretized sampling on the plurality of segmented paths to obtain a plurality of path points includes: performing discretized sampling on the plurality of segmented routes to obtain a plurality of sampling points; When it is determined that the plurality of sampling points are all located within the corresponding field of view of the visual sensor, the plurality of sampling points are determined as a plurality of path points; in determining the plurality of sampling points, there are those that are not located in the field of view In the case of sampling points, the current yaw angle of the drone is obtained, and the current yaw angle is adjusted until the multiple sampling points are all within the field of view.

According to a path planning method provided by the present invention, the determination that the UAV collides with the target segment path corresponding to the target way point includes: in the case of determining that there is an obstacle on the target segment path corresponding to the target way point, If it is detected that the UAV will collide with the obstacle, it is determined that the UAV collides on the target segmented path.

According to a path planning method provided by the present invention, the acquisition of the global environment information corresponding to the unknown environment, and determining the current path corresponding to the start position and the end position according to the global environment information include: acquiring the global environment information corresponding to the unknown environment ;According to the global environment information, determine the global grid map, each grid in the global grid map indicates that the current position is an obstacle or the passable area of the UAV; according to the global grid map, determine the starting The first grid corresponding to the position and the second grid corresponding to the end position; determine the current path corresponding to the first grid and the second grid.

The present invention also provides a path planning device, including:

The obtaining module is used to obtain the global environment information corresponding to the unknown environment;

a path determination module, configured to determine the current path corresponding to the start position and the end position according to the global environment information;

The processing module is used to segment the current path to obtain a plurality of segmented paths, and to sample the plurality of segmented paths to obtain a plurality of path points; In the case of a collision between segment paths, the local environment information corresponding to the target segment path acquired by the visual sensor is used to update the global environment information to obtain new global environment information. The target path point is any one of the multiple path points. waypoint;

The path determination module is further configured to determine the target path corresponding to the start position and the end position by using the A* algorithm based on the new global environment information.

Optionally, the path determination module is specifically configured to determine a start position and an end position from the global environment information; connect the start position and the end position to obtain a straight line path.

Optionally, the processing module is specifically used to segment the straight path by using the length of the visual cone corresponding to the visual sensor during the process of the UAV executing the straight path to obtain multiple segmented paths. The visual sensor It is set on the unmanned aerial vehicle; performing discretization sampling on the plurality of segmented paths to obtain a plurality of path points.

Optionally, the processing module is specifically configured to perform discretized sampling on the multiple segmented paths according to a preset map resolution to obtain multiple path points.

Optionally, the processing module is specifically configured to perform discrete sampling on the plurality of segmented paths to obtain a plurality of sampling points; when it is determined that the plurality of sampling points are located within the corresponding field of view of the visual sensor, Determining the plurality of sampling points as a plurality of waypoints; in the case of determining that there are sampling points not within the field of view among the plurality of sampling points, obtaining the current yaw angle of the drone, and adjusting the current yaw angle. Yaw angle until the plurality of sampling points are within the field of view.

Optionally, the processing module is specifically used to determine that the UAV will collide with the obstacle when it is determined that there is an obstacle on the target segment path corresponding to the target waypoint. A collision occurred on the target segment path.

Optionally, the path determination module is specifically used to obtain global environment information corresponding to an unknown environment; determine a global grid map according to the global environment information, and each grid in the global grid map indicates that the current position is an obstacle Or the passable area of the UAV; according to the global grid map, determine the first grid corresponding to the starting position and the second grid corresponding to the end position; determine the correspondence between the first grid and the second grid the current path of .

The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes the program, the path planning method described above is implemented. .

The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, any one of the path planning methods described above can be implemented.

The present invention also provides a computer program product, including a computer program, when the computer program is executed by a processor, any one of the path planning methods described above is implemented.

The path planning method, device, electronic equipment, and storage medium provided by the present invention determine the current path corresponding to the start position and the end position according to the global environment information corresponding to the unknown environment by obtaining the global environment information; The path is segmented to obtain a plurality of segmented paths, and the plurality of segmented paths are sampled to obtain a plurality of waypoints; when it is determined that the UAV collides with the target segmented path corresponding to the target waypoint Updating the global environment information by using the local environment information corresponding to the target segment path obtained by the visual sensor to obtain new global environment information, the target path point being any path point among the plurality of path points; Based on the new global environment information, an A* algorithm is used to determine a target path corresponding to the start position and the end position. This method is used to solve the problem that although the electronic equipment in the prior art can find the flight path between the starting position and the terminal position for the UAV, due to the large search time for planning the flight path and the path planning method used has certain limitations. Due to the limitations of the electronic device, the flight path obtained by the electronic device is not the defect of the optimal path between the starting position and the end position, so that the electronic device can control the UAV when the UAV is in an unknown environment. The executed current path is segmented, and the A* algorithm is used to obtain the target path between the start position and the end position of the UAV. The planning time of the target path is short, and it is a better path.

Description of drawings

In order to more clearly illustrate the present invention or the technical solutions in the prior art, the accompanying drawings that need to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings in the following description are the present invention. For some embodiments of the invention, those skilled in the art can also obtain other drawings based on these drawings without creative effort.

Fig. 1 is a schematic flow chart of the path planning method provided by the present invention;

Fig. 2a is one of the schematic diagrams of the global environment information provided by the present invention;

Fig. 2b is the second schematic diagram of the global environment information provided by the present invention;

Figure 2c is one of the schematic diagrams of the target path provided by the present invention;

Figure 2d is the second schematic diagram of the target path provided by the present invention;

Fig. 2e is the third schematic diagram of the global environment information provided by the present invention;

Fig. 2f is the third schematic diagram of the target path provided by the present invention;

Fig. 2g is the fourth schematic diagram of the target path provided by the present invention;

Fig. 3 is a schematic structural diagram of a path planning device provided by the present invention;

Fig. 4 is a schematic structural diagram of an electronic device provided by the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

As shown in Figure 1, it is a schematic flow chart of the path planning method provided by the present invention, which may include:

101. Acquire global environment information corresponding to the unknown environment, and determine a current path corresponding to a start location and an end location according to the global environment information.

Wherein, the global environment information is information corresponding to an unknown environment.

For the UAV, the above global environment information is assumed to be a known environment information.

Wherein, the global environment information may include a plurality of locations, and the plurality of locations may include but not limited to: the starting location where the UAV is about to depart, the destination location where the UAV is going to arrive, and the location of obstacle points.

After the electronic device obtains the global environment information corresponding to the unknown environment, it can randomly obtain two positions from the multiple positions included in the global environment information, which are the start position and the end position; The starting position and the end position are randomly connected to obtain the current path corresponding to the starting position and the end position.

Optionally, the number of current paths corresponding to these two locations may be at least one.

Exemplarily, as shown in FIG. 2a, it is a schematic diagram of the global environment information provided by the present invention. In FIG. 2a, the global environment information includes multiple locations, represented by black solid circles. The electronic device obtains the starting location A and the ending location B from the multiple locations, and converts the starting location A and the ending location B into 4 different ways to connect, respectively can get the first path, the second path, the third path and the fourth path, the first path, the second path, the third path and the fourth path are different from each other same.

Optionally, the electronic device determines the current path corresponding to the start position and the end position according to the global environment information, which may include: the electronic device determines the start position and the end position from the global environment information; the electronic device determines the start position and the end position The end positions are connected to obtain a straight line path.

After the electronic device determines the start position and the end position from the global environment information, it can directly connect the two positions without considering whether there is an obstacle between the two positions, and directly obtain the start position and the end position Corresponding straight line path. That is, the electronic device can effectively obtain the straight-line path corresponding to the starting position and the end point without searching and traversing the global environment information, thereby not only reducing the planning time of the straight-line path, but also improving the speed of the straight-line path. acquisition efficiency.

Optionally, the electronic device obtains the global environment information corresponding to the unknown environment, and determines the current path corresponding to the start position and the end position according to the global environment information, which may include: the electronic device obtains the global environment information corresponding to the unknown environment in the current area; The electronic device determines the global grid map according to the global environment information; the electronic device determines the first grid corresponding to the starting position and the second grid corresponding to the end position according to the global grid map; the electronic device determines the first grid grid and the current path corresponding to the second grid.

Wherein, each grid in the global grid map indicates that the current position is an obstacle or a passable area of the UAV.

Wherein, the current area refers to the area where the drone is currently located.

The electronic device can simulate the current environment of the UAV to obtain a grid discrete environment, that is, a global grid map, and then determine the current path corresponding to the starting position and the end position for the global grid map.

102. Segment the current path to obtain multiple segmented paths, and sample the multiple segmented paths to obtain multiple path points.

After the electronic device obtains the current path, it can perform segmentation processing and sampling processing on the current path to obtain multiple discrete path points, so that the electronic device can accurately update the global environment information subsequently.

Optionally, the electronic device segments the current path to obtain multiple segmented paths, and samples the multiple segmented paths to obtain multiple path points, which may include: the process of the electronic device executing a straight-line path on the UAV In the method, the linear path is segmented using the length of the visual cone corresponding to the visual sensor to obtain multiple segmented paths; the electronic device performs discretized sampling on the multiple segmented paths to obtain multiple path points.

Among them, the vision sensor is set on the drone.

The vision sensor is a sensor with a time of flight (Time Of Flight, TOF) function, that is, a sensor that can measure the depth of the environment.

The length of the viewing cone refers to the length of the range that the shooting field of view of the visual sensor can reach, that is, the length of the field of view of the visual sensor.

Optionally, the lengths of viewing cones corresponding to different visual sensors may be the same or different, which is not specifically limited here.

Optionally, the vision sensor may be a Red Green Blue–Depth (RGB-D) camera or a depth camera, etc.

After the electronic device obtains the straight-line path, it can control the UAV to fly along the straight-line path; then, the electronic device can divide the straight-line path evenly by using the length of the cone of view corresponding to the visual sensor to obtain multiple segmented paths. Among these multiple segmented paths, the first endpoint of the first segmented path may be the starting position of the drone, and the second endpoint of the first segmented path is the first endpoint of the second segmented path, The second end point of the second segment path is the first end point of the third segment path, the first segment path is adjacent to the second segment path, and the second segment path is adjacent to the third segment path The paths are adjacent, and so on, and the second end point of the last path segment may be the terminal position of the drone.

Next, the electronic device uses the visual sensor to perform discretization sampling on the multiple continuous segmented paths to obtain multiple discrete path points, so that the electronic device can traverse the multiple discrete path points subsequently, thereby realizing Accurately update global environment information.

Optionally, the electronic device may use the first segment path as the first path point, may use the second segment path as the second path point, and so on, may use the Nth segment path as the Nth path point, the The N segment path is the last segment path among the plurality of segment paths, and N is an integer greater than or equal to 2.

Optionally, the electronic device performs discrete sampling on multiple segmented paths to obtain multiple path points, which may include but not limited to at least one of the following implementations:

Implementation mode 1: The electronic device performs discretized sampling on multiple segmented paths according to a preset map resolution to obtain multiple path points.

Optionally, the preset map resolution may be set by the electronic device before leaving the factory, or may be user-defined, which is not specifically limited here.

Implementation 2: The electronic device performs discretized sampling on multiple segmented paths to obtain multiple sampling points; when the electronic device determines that the multiple sampling points are within the corresponding field of view of the visual sensor, the multiple sampling points Determined as multiple waypoints; the electronic device obtains the current yaw angle of the drone and adjusts the current yaw angle until multiple The sampling points are all within the field of view.

Wherein, the current yaw angle refers to the angle between the current heading of the UAV and the heading corresponding to the previously acquired straight path.

After the electronic device acquires multiple discrete sampling points, it can determine whether the multiple sampling points are within the field of view corresponding to the visual sensor; if the multiple sampling points are within the field of view, then it means that the drone's The deviation between the current flight path and the previously obtained straight path is relatively small, so the multiple sampling points obtained by the electronic device are relatively accurate, and these multiple sampling points can be directly determined as the path points; if the multiple If there is a sampling point that is not within the field of view in the sampling point, the sampling point can be called the target point. Then, it means that the flight path of the UAV at the target point has a large deviation from the straight path. Therefore, the electronic The target point obtained by the device is inaccurate. At this time, the electronic device needs to obtain the angle between the current heading corresponding to the flight path of the drone at the target point and the heading corresponding to the straight line path, and adjust the clip angle, so that the target point can be located within the field of view, and then the electronic device can determine the currently acquired multiple sampling points as multiple path points.

Wherein, the number of target points is less than or equal to the number of sampling points, and the number of the target point is at least one.

103. When it is determined that the UAV collides with the target segment path corresponding to the target waypoint, use the local environment information corresponding to the target segment path acquired by the visual sensor to update the global environment information to obtain new global environment information.

Wherein, the target waypoint is any waypoint among the plurality of waypoints.

Optionally, the number of the target waypoint is at least one.

Optionally, before step 103, the method may also include but not limited to the following implementations:

Implementation 1: The electronic device uses a visual sensor to obtain the path environment information corresponding to the segmented path corresponding to each of the multiple path points; the electronic device determines that there are no obstacles in the path environment information corresponding to the target segmented path In the case of , the path environment information is determined as the local environment information corresponding to the target segment path.

Implementation mode 2: the electronic device uses a visual sensor to obtain the path environment information corresponding to the segmented path corresponding to each of the multiple path points; the electronic device determines that there are obstacles in the path environment information corresponding to the target segmented path but If there is no collision with the obstacle, the path environment information is determined as the local environment information corresponding to the target segmented path.

That is to say, regardless of the implementation mode 1 or the implementation mode 2, the local environment information corresponding to each segmented path obtained by the electronic device will not collide with the drone.

Under the global environmental information, the electronic device controls the UAV to start from the starting position and fly according to the current path. When it is determined that the UAV collides with the target segment path corresponding to the target path point, it can obtain the visual sensor before The local environment information corresponding to the segmented path of the target, there are obstacles in the local environment information; then, the electronic device replaces the global environment information with the local environment information to obtain new global environment information, in the new global environment information In the environmental information, so that the follow-up electronic equipment can use the A* algorithm to re-plan the flight path of the UAV, so that the UAV can avoid obstacles in the segmented path of the target, so that the UAV and the UAV Obstacles do not collide.

Optionally, the electronic device determining that the UAV collides with the target segment path corresponding to the target way point may include: when the electronic device determines that there is an obstacle on the target segment path corresponding to the target way point, if the electronic device detects If the UAV collides with the obstacle, it is determined that the UAV collides on the target segmented path.

If there is an obstacle on the target segmented path corresponding to the target waypoint, then the UAV will collide with the obstacle while passing the target segmented path. At this time, the electronic device can determine that the unmanned The aircraft collided on the target segment path.

Optionally, the electronic device may control the UAV to fly according to the current route and arrive at the terminal position when it is determined that the UAV does not collide at all the waypoints.

Optionally, the electronic device can control the UAV to fly according to the current route and reach the end position when it is determined that the UAV has not collided with all the way points, which may include: the electronic device determines that the UAV is in all paths When there is no collision between the points, the UAV can be controlled to fly along a straight line and reach the end position.

In this way, the steps and time of path planning between the start position and the end position of the UAV can be saved, thereby improving the flight efficiency of the UAV.

104. Based on the new global environment information, use the A* algorithm to determine the target path corresponding to the start position and the end position.

Wherein, the A* algorithm involved in the present invention refers to a graph search algorithm, an effective direct search method for solving the shortest path in a static unknown environment. In the process of searching for the target path, the A* algorithm can evaluate the feasibility of multiple path points, select the path point with the smallest cost value as the node for the next expansion, and then continue from the next node until reaching the end point.

The target path refers to the optimal path for the UAV to fly from the starting position to the final position. The target path may include the current path between the starting position and the position point where the target segment path collides, and the path between the colliding position point and the end position obtained by using the A* algorithm; it may also include the actual position The first current path between the location points colliding with the first target segment path, the second current path between the location points where the first current path collides with the second target segment path, and using the A* algorithm The obtained path between the location where the collision occurs and the end point corresponding to the second current path is obtained. That is, the target path is composed of paths obtained by the two methods respectively.

Optionally, the better path may be the best path.

Optionally, after step 104, the method may also include but not limited to at least one of the following implementation manners:

Implementation method 1: The electronic device controls the UAV to execute the target path and reach the end position.

The electronic equipment controls the UAV to fly on a better path, and can reach the end position quickly and accurately.

Implementation mode 2: the electronic device outputs the target path.

Optionally, the electronic device outputs the target path, which may include but not limited to at least one of the following methods:

Mode 1: The electronic device outputs the target path in the form of an image.

Method 2: The electronic device sends the target path to other associated devices, so that the electronic device and the other associated devices can simultaneously control the UAV to fly along the target path.

Either way, the user using the electronic device can obtain the target path corresponding to the start position and the end position in time.

Implementation mode 3: the electronic device stores the target path.

After the electronic device stores the target path, if the drone needs to move from the starting position to the end position again, then the electronic device only needs to obtain the stored target path corresponding to the starting position and the end position, In this way, the purpose of saving the acquisition time of the target path is achieved.

Exemplary, exemplary, as shown in Figure 2b, is a schematic diagram of the global environment information provided by the present invention; as shown in Figure 2c, is a schematic diagram of the target path provided by the present invention; as shown in Figure 2d, is a schematic diagram of the present invention Schematic diagram of the provided target path.

In Figure 2b, the global environment information includes multiple obstacle locations, represented by cylinders.

The target paths in Figure 2c and Figure 2d are collision-free paths for the UAV to fly from the starting position to the end position under the global environment information shown in Figure 2b. In FIG. 2c, the target path is obtained by the electronic device based on the path planning method provided by the present invention; in FIG. 2d, the target path is obtained by the electronic device based on the traditional A* algorithm, and the target path has obvious turning phenomenon.

As shown in Table 1, it is a parameter comparison table corresponding to Figure 2c and Figure 2d respectively provided by the present invention;

Table 1:

It can be seen from Table 1 that the parameters corresponding to the target path provided by the present invention are better than the parameters corresponding to the target path of the traditional traditional A* algorithm.

Exemplarily, as shown in Figure 2e, it is a schematic diagram of the global environment information provided by the present invention; as shown in Figure 2f, it is a schematic diagram of the target path provided by the present invention; as shown in Figure 2g, it is the target path provided by the present invention schematic diagram.

In Figure 2e, the global environment information includes multiple obstacle locations, represented by black solid rectangles, and these obstacle locations are relatively messy.

The target paths in Figure 2f and Figure 2g are collision-free paths for the UAV to fly from the initial position to the final position under the global environment information shown in Figure 2e. In FIG. 2f, the target path is obtained by the electronic device based on the path planning method provided by the present invention; in FIG. 2g, the target path is obtained by the electronic device based on the traditional A* algorithm, and the target path has obvious turning phenomenon.

As shown in Table 2, it is a parameter comparison table corresponding to Figure 2f and Figure 2g respectively provided by the present invention;

Table 2:

It can be seen from Table 2 that the parameters corresponding to the target path provided by the present invention are better than the parameters corresponding to the target path of the traditional traditional A* algorithm.

In the embodiment of the present invention, by obtaining the global environment information corresponding to the unknown environment, and according to the global environment information, determine the current path corresponding to the start position and the end position; segment the current path to obtain multiple segmented paths, and Sampling multiple segmented paths to obtain multiple path points; in the case that the UAV is determined to collide with the target segmented path corresponding to the target waypoint, use the local environment information corresponding to the target segmented path obtained by the visual sensor Update the global environment information to obtain new global environment information, and the target path point is any path point among multiple path points; based on the new global environment information, use the A* algorithm to determine the target path corresponding to the start position and the end position . This method is used to solve the problem that although the electronic equipment in the prior art can find the flight path between the starting position and the terminal position for the UAV, due to the large search time for planning the flight path and the path planning method used has certain limitations. Due to the limitations of the electronic device, the flight path obtained by the electronic device is not the defect of the optimal path between the starting position and the end position, so that the electronic device can control the UAV when the UAV is in an unknown environment. The executed current path is segmented, and the A* algorithm is used to obtain the target path between the start position and the end position of the UAV. The planning time of the target path is short, and it is a better path.

The path planning device provided by the present invention is described below, and the path planning device described below and the path planning method described above can be referred to in correspondence.

As shown in Figure 3, it is a schematic structural diagram of the path planning device provided by the present invention, which may include:

An acquisition module 301, configured to acquire global environment information corresponding to an unknown environment;

A route determination module 302, configured to determine the current route corresponding to the start position and the end position according to the global environment information;

The processing module 303 is used to segment the current path to obtain a plurality of segmented paths, and sample the plurality of segmented paths to obtain a plurality of path points; In the case of a collision between the segmented paths, the local environment information corresponding to the target segmented path acquired by the visual sensor is used to update the global environment information to obtain new global environment information. The target path point is any of the multiple path points. a waypoint;

The route determination module 302 is further configured to determine the target route corresponding to the start position and the end position by using the A* algorithm based on the new global environment information.

Optionally, the path determination module 302 is specifically configured to determine a start position and an end position from the global environment information; connect the start position and the end position to obtain a straight line path.

Optionally, the processing module 303 is specifically configured to segment the straight line path by using the length of the visual cone corresponding to the visual sensor during the process of executing the straight line path by the UAV to obtain multiple segmented paths. It is set on the unmanned aerial vehicle; performing discretization sampling on the plurality of segmented paths to obtain a plurality of path points.

Optionally, the processing module 303 is specifically configured to perform discretization sampling on the multiple segmented routes according to a preset map resolution, to obtain multiple route points.

Optionally, the processing module 303 is specifically configured to perform discretized sampling on the multiple segmented paths to obtain multiple sampling points; when it is determined that the multiple sampling points are all located within the field of view corresponding to the visual sensor, Determining the plurality of sampling points as a plurality of waypoints; in the case of determining that there are sampling points not within the field of view among the plurality of sampling points, obtaining the current yaw angle of the drone, and adjusting the current yaw angle. Yaw angle until the plurality of sampling points are within the field of view.

Optionally, the processing module 303 is specifically configured to, in the case of determining that there is an obstacle on the target segment path corresponding to the target waypoint, if it is detected that the UAV will collide with the obstacle, then determine that the UAV A collision occurred on the target segment path.

Optionally, the obtaining module 301 is specifically used to obtain global environment information corresponding to the unknown environment;

The path determination module 302 is specifically used to determine a global grid map according to the global environment information, and each grid in the global grid map indicates that the current position is an obstacle or a passable area of the UAV; according to the global The grid map is to determine the first grid corresponding to the starting position and the second grid corresponding to the end position; determine the current path corresponding to the first grid and the second grid.

FIG. 4 illustrates a schematic diagram of the physical structure of an electronic device. As shown in FIG. 4, the electronic device may include: a processor (processor) 410, a communication interface (Communications Interface) 420, a memory (memory) 430 and a communication bus 440, Wherein, the processor 410 , the communication interface 420 , and the memory 430 communicate with each other through the communication bus 440 . The processor 410 can call the logic instructions in the memory 430 to execute the path planning method, the method includes: acquiring global environment information corresponding to the unknown environment, and determining the current path corresponding to the start position and the end position according to the global environment information; Segment the current path to obtain multiple segmented paths, and sample the multiple segmented paths to obtain multiple path points; when it is determined that the UAV collides with the target segmented path corresponding to the target path point In this case, the global environment information is updated by using the local environment information corresponding to the target segmented path obtained by the visual sensor to obtain new global environment information, and the target path point is any path point in the plurality of path points; based on the The new global environment information uses the A* algorithm to determine the target path corresponding to the start position and the end position.

In addition, the above logic instructions in the memory 430 may be implemented in the form of software function units and be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other various media that can store program codes. .

On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can Executing the path planning method provided by the above methods, the method includes: obtaining the global environment information corresponding to the unknown environment, and determining the current path corresponding to the start position and the end position according to the global environment information; segmenting the current path , to obtain multiple segmented paths, and sample the multiple segmented paths to obtain multiple path points; when it is determined that the UAV collides with the target segmented path corresponding to the target path point, use the visual sensor to obtain The local environment information corresponding to the target segmented path updates the global environment information to obtain new global environment information, and the target path point is any path point in the plurality of path points; based on the new global environment information, using The A* algorithm determines the target path corresponding to the start position and the end position.

In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the path planning method provided by the above-mentioned methods is implemented, and the method includes: Obtain the global environment information corresponding to the unknown environment, and determine the current path corresponding to the starting position and the end position according to the global environment information; segment the current path to obtain multiple segmented paths, and determine the multiple segmented paths The path is sampled to obtain multiple path points; when it is determined that the UAV collides with the target segment path corresponding to the target path point, the local environment information corresponding to the target segment path obtained by the visual sensor is used to update the global environment Information to obtain new global environment information, the target waypoint is any one of the multiple waypoints; based on the new global environment information, use the A* algorithm to determine the corresponding starting position and the end position Target path.

The device embodiments described above are only illustrative, and 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 it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without any creative effort.

Through the above description of the implementations, those skilled in the art can clearly understand that each implementation can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of software products, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic discs, optical discs, etc., including several instructions to make a computer device (which may be a personal computer, server, or network device, etc.) execute the methods described in various embodiments or some parts of the embodiments.

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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or equivalent replacements are made to some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims (10)

1. A path planning method, characterized in that, comprising: Obtain global environment information corresponding to the unknown environment, and determine the current path corresponding to the start position and the end position according to the global environment information; Segmenting the current path to obtain a plurality of segmented paths, and sampling the plurality of segmented paths to obtain a plurality of path points; When it is determined that the UAV collides with the target segment path corresponding to the target way point, the local environment information corresponding to the target segment path acquired by the visual sensor is used to update the global environment information to obtain new global environment information , the target waypoint is any one of the plurality of waypoints; Based on the new global environment information, an A* algorithm is used to determine a target path corresponding to the start position and the end position. 2. The method according to claim 1, wherein the determining the current path corresponding to the start position and the end position according to the global environment information comprises: Determining a start position and an end position from the global environment information; Connect the start position and the end position to obtain a straight line path. 3. The method according to claim 2, wherein the current path is segmented to obtain a plurality of segmented paths, and the plurality of segmented paths are sampled to obtain a plurality of path points ,include: During the process of the UAV executing the straight path, the straight path is segmented using the length of the visual cone corresponding to the visual sensor to obtain a plurality of segmented paths, and the visual sensor is arranged on the UAV; Discretization sampling is performed on the multiple segmented paths to obtain multiple path points. 4. The method according to claim 3, wherein said performing discretization sampling on said plurality of segmented paths to obtain a plurality of path points comprises: According to the preset map resolution, discretization sampling is performed on the multiple segmented paths to obtain multiple path points. 5. The method according to claim 3 or 4, wherein said performing discretized sampling on said plurality of segmented paths to obtain a plurality of path points comprises: performing discretized sampling on the plurality of segmented paths to obtain a plurality of sampling points; In the case where it is determined that the plurality of sampling points are located within the field of view corresponding to the visual sensor, determining the plurality of sampling points as a plurality of waypoints; In the case of determining that there are sampling points not located within the field of view among the plurality of sampling points, obtain the current yaw angle of the drone, and adjust the current yaw angle until the plurality of sampling points The sampling points are all within the field of view. 6. The method according to any one of claims 1-4, wherein said determining that the UAV collides with the target segment path corresponding to the target waypoint comprises: In the case of determining that there is an obstacle on the target segmented path corresponding to the target waypoint, if it is detected that the UAV collides with the obstacle, it is determined that the UAV collides with the target segmented path . 7. The method according to any one of claims 1-4, characterized in that the acquisition of global environment information corresponding to the unknown environment, and determining the current location corresponding to the start position and the end position according to the global environment information path, including: Obtain the global environment information corresponding to the unknown environment; According to the global environment information, determine a global grid map, each grid in the global grid map indicates that the current position is an obstacle or a passable area of the drone; According to the global grid map, determine the first grid corresponding to the starting position and the second grid corresponding to the end position; Determine the current path corresponding to the first grid and the second grid. 8. A path planning device, characterized in that it comprises: The obtaining module is used to obtain the global environment information corresponding to the unknown environment; a path determination module, configured to determine the current path corresponding to the start position and the end position according to the global environment information; A processing module, configured to segment the current path to obtain a plurality of segmented paths, and sample the plurality of segmented paths to obtain a plurality of path points; When the target segmental path collides, the local environment information corresponding to the target segmental path acquired by the visual sensor is used to update the global environment information to obtain new global environment information, and the target path points are the multiple any of the waypoints; The path determination module is further configured to determine a target path corresponding to the start position and the end position by using the A* algorithm based on the new global environment information. 9. An electronic device, comprising: a memory, a processor, and a computer program stored on the memory and operable on the processor, characterized in that, when the processor executes the program, the computer program according to claim 1 is realized. The path planning method described in any one of 1 to 7. 10. A non-transitory computer-readable storage medium, on which a computer program is stored, wherein, when the computer program is executed by a processor, the path planning method according to any one of claims 1 to 7 is implemented.

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