CN117889866A - Navigation path planning method, device and storage medium - Google Patents
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Abstract
The application provides a navigation path planning method, equipment and a storage medium, belonging to the field of navigation, wherein the method comprises the following steps: acquiring a target map and a navigation task, wherein the target map comprises a map grid and map topological edges; planning a navigation path in the target map based on the navigation task to obtain a candidate navigation path; acquiring grid distance and topology distance of the candidate navigation path in the target map; determining a cost value of the candidate navigation path according to the grid distance and the topology distance of the candidate navigation path; and determining a target navigation path from the candidate navigation paths according to the cost value of the candidate navigation paths. The method and the device can plan the safer and more reliable target navigation path, and greatly improve the reliability and controllability of navigation path planning.
Description
Technical Field
The present disclosure relates to the field of navigation technologies, and in particular, to a navigation path planning method, apparatus, and storage medium.
Background
With the development of social economy and science and technology, more and more mobile robots are moving into the life and work of people, from various home sweeping robots to various service and meal delivery robots in service places, and to logistics robots in logistics and industrial fields. The navigation path planning of the robot is an important ring in the operation process, and the high-quality navigation path can improve the working efficiency of the robot and reduce the energy consumption so as to show the value of the robot. At present, the planned robot navigation path has the defects of poor controllability and poor safety, so that the running of the robot is at great risk.
Therefore, how to plan a safe and reliable navigation path is a problem to be solved at present.
Disclosure of Invention
The main purpose of the application is to provide a navigation path planning method, equipment and storage medium, aiming at planning a safe and reliable navigation path so as to improve the operation safety and reliability of a robot.
In a first aspect, the present application provides a navigation path planning method, including the steps of:
acquiring a target map and a navigation task, wherein the target map comprises a map grid and map topological edges;
planning a navigation path in the target map based on the navigation task to obtain a candidate navigation path;
acquiring grid distance and topology distance of the candidate navigation path in the target map;
determining a cost value of the candidate navigation path according to the grid distance and the topology distance of the candidate navigation path;
and determining a target navigation path from the candidate navigation paths according to the cost value of the candidate navigation paths.
In a second aspect, the present application further provides a terminal device, the terminal device comprising a processor, a memory, and a computer program stored on the memory and executable by the processor, wherein the computer program when executed by the processor implements the steps of the navigation path planning method as described above.
In a third aspect, the present application also provides a computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of a navigation path planning method as described above.
The application provides a navigation path planning method, equipment and a storage medium. The cost value of the candidate navigation path can be accurately determined according to the grid distance and the topological distance of the candidate navigation path, and the safer and more reliable target navigation path can be accurately determined from the candidate navigation path according to the cost value of the candidate navigation path, so that the reliability and the controllability of navigation path planning are greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a navigation path planning method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a scenario in which the navigation path planning method according to the present embodiment is implemented;
FIG. 3 is a flow chart illustrating sub-steps of step S101 of the navigation path planning method of FIG. 1;
fig. 4 is another schematic view of a scenario for implementing the navigation path planning method provided in the present embodiment;
fig. 5 is a schematic view of another scenario for implementing the navigation path planning method provided in the present embodiment;
FIG. 6 is a schematic diagram of another scenario in which the navigation path planning method according to the present embodiment is implemented;
FIG. 7 is a flow chart illustrating sub-steps of step S102 of the navigation path planning method of FIG. 1;
FIG. 8 is a flow chart illustrating sub-steps of step S103 of the navigation path planning method of FIG. 1;
FIG. 9 is a schematic diagram of another scenario in which the navigation path planning method according to the present embodiment is implemented;
FIG. 10 is a schematic diagram of another scenario in which the navigation path planning method according to the present embodiment is implemented;
FIG. 11 is a schematic diagram of another scenario in which the navigation path planning method according to the present embodiment is implemented;
fig. 12 is a schematic block diagram of a structure of a terminal device according to an embodiment of the present application.
The realization, functional characteristics and advantages of the present application will be further described with reference to the embodiments, referring to the attached drawings.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
The flow diagrams depicted in the figures are merely illustrative and not necessarily all of the elements and operations/steps are included or performed in the order described. For example, some operations/steps may be further divided, combined, or partially combined, so that the order of actual execution may be changed according to actual situations.
The embodiment of the application provides a navigation path planning method, navigation path planning equipment and a storage medium. The navigation path planning method can be applied to terminal equipment, and the terminal equipment can be electronic equipment such as mobile phones, tablet computers, notebook computers, desktop computers, personal digital assistants and the like. For example, the terminal device may be a mobile phone, where the mobile phone obtains a target map and a navigation task, and the target map includes a map grid and a map topology edge; planning a navigation path in a target map based on the navigation task to obtain a candidate navigation path; acquiring grid distance and topology distance of a candidate navigation path in a target map; determining a cost value of the candidate navigation path according to the grid distance and the topology distance of the candidate navigation path; and determining a target navigation path from the candidate navigation paths according to the cost value of the candidate navigation paths.
In some embodiments, the navigation path planning method may be applied to a mobile robot, which may be a medical robot, a military robot, a disabled-aid robot, a cleaning robot, a cargo robot, or the like. For example, the mobile robot is a cargo robot, the cargo robot acquires a target map and a navigation task, and the target map comprises a map grid and map topological edges; planning a navigation path in a target map based on the navigation task to obtain a candidate navigation path; acquiring grid distance and topology distance of a candidate navigation path in a target map; determining a cost value of the candidate navigation path according to the grid distance and the topology distance of the candidate navigation path; and determining a target navigation path from the candidate navigation paths according to the cost value of the candidate navigation paths.
Some embodiments of the present application are described in detail below with reference to the accompanying drawings. The following embodiments and features of the embodiments may be combined with each other without conflict.
Referring to fig. 1, fig. 1 is a flow chart of a navigation path planning method according to an embodiment of the present application.
As shown in fig. 1, the navigation path planning method includes steps S101 to S105.
Step S101, acquiring a target map and a navigation task, wherein the target map comprises a map grid and map topological edges.
The target map includes a map grid and a map topology edge, the map grid is a grid path area set in the target map, the map topology edge is a topology edge path area set in the target map, the map grid and the map topology edge can be set according to actual conditions, and the embodiment of the invention is not limited in particular.
The navigation task comprises a starting point and an end point of navigation, and is used for providing navigation parameters for the mobile robot; the starting point is the starting point of the navigation task and the end point is the destination of the navigation task. The navigation task may direct the mobile robot to move from a start point to an end point in the target map.
As shown in fig. 2, fig. 2 is a schematic view of a scenario for implementing the navigation path planning method according to the present embodiment. The target map in fig. 2 includes room 1, room 2, room 3, and room 4, and a map grid 10 is provided in the target map, the map grid 10 connecting navigation paths of the room 1, room 2, room 3, and room 4. A map topology edge 20 is further disposed in the target map, the map topology edge 20 is disposed in the room 3, and the map topology edge 20 is connected with the map grid 10, the map topology edge 20 includes a map topology edge influence range 21, and the map topology edge influence range 21 is used for representing that a navigation path located in the map topology edge influence range can be a map topology edge.
The map grid and the map topological edge are integrated through the setting of the target map, the purpose of navigating in the map grid and the map topological edge can be achieved without switching the map, the problem that a path cannot be defined by the map grid and the defect that the map topological edge cannot avoid an obstacle are solved, and therefore the safety and the reliability of mobile robot navigation are achieved.
In an embodiment, as shown in fig. 3, fig. 3 is a schematic flow chart of sub-steps of step S101 of the navigation path planning method in fig. 1, and step S101 includes sub-steps S1011 to S1012.
In the substep S1011, map topological edges and map grids are obtained, and coordinates of each map grid and coordinates of each topological point in each map topological edge are obtained.
Acquiring a first map comprising a map grid and a second map comprising map topological edges; the first map and the second map have the same map area, which may be set according to actual situations, and the embodiment of the present invention is not limited to this, for example, the same map area may be the same in all map areas, or may be the same in part map areas, as shown in fig. 4, fig. 4 is another schematic view of a scene in which the navigation path planning method provided in the embodiment is implemented, and fig. 4 is a first map, where the first map includes a room 1, a room 2, a room 3, and a room 4, and the first map includes a map grid 10; as shown in fig. 5, the second map includes room 1, room 2, room 3, and room 4, the second map includes map topology side 20 and map topology side 30, the map topology side 20 includes map topology side influence range 21, and the map topology side 30 includes map topology side influence range 31. As can be seen from fig. 4 and 5, all map areas of the first map and the second map are the same.
In an embodiment, obtaining a topology attribute of each map topology edge to be built, wherein the topology attribute at least comprises a topology direction and a topology edge influence range; and constructing map topological edges in the middle of the map according to the topological attribute of each map topological edge to be constructed, and generating the map topological edges. Map topology edges can be accurately established through topology properties.
It should be noted that, the topology direction is used for representing the path direction of the map topology edge, the topology direction includes one-way and two-way, the topology edge influence range is used for representing the width of the map topology edge, the larger the topology edge influence range is, the wider the map topology edge is, and therefore the more lanes the map topology edge can plan can be determined. If the topological distance is set as the limit value, determining that the topological direction is unidirectional; if the topological distance is not set to be the limit value, the topological direction is determined to be bidirectional.
In an embodiment, when the topological distance in the first topological direction of the map topological edge is approaching zero and the topological distance in the second topological direction is approaching infinity, determining that the map topological edge is unidirectional; and determining that the map topological edge is bidirectional under the condition that the topological distance of the first topological direction of the map topological edge is approaching zero and the topological distance of the second topological direction is approaching zero. By setting the topological distance of the map topological edge in the topological direction, the direction of the map topological edge can be accurately set.
In an embodiment, the topology direction may be set by user-definition, or may be adjusted by a mobile robot according to an actual operation environment, for example, when the number of mobile robots driving on the map topology edge is greater than or equal to a preset number, the map topology edge is set to be unidirectional, and when the number of mobile robots driving on the map topology edge is less than the preset number, the map topology edge is set to be bidirectional. In some embodiments, the map topology edge is set to bidirectional for a first period of time and to unidirectional for a second period of time.
For example, in the case where the number of mobile robots traveling while the map topology is greater than or equal to 5, the map topology side is set to be unidirectional, and in the case where the number of mobile robots traveling while the map topology is less than 5, the map topology side is set to be bidirectional. Map topology edges are set to be bidirectional at time 0 to 7 points and unidirectional at time 7 to 24 points.
As shown in fig. 6, fig. 6 is a schematic diagram of another scenario for implementing the navigation path planning method provided in the present embodiment. The map topology edge in fig. 6 includes a first topology direction 41 and a second topology direction 42, and in the case where the topology distance of the first topology direction 41 is close to zero and the topology distance of the second topology direction 42 is close to zero, it is determined that the map topology edge is bidirectional. It will be appreciated that the first topological direction 41 is the direction of travel of the first direction of the map topological edge and the second topological direction 42 is the direction of travel of the second direction of the map topological edge.
In one embodiment, the topological edge influence range is used for representing the width of the topological edge of the map, and the larger the topological edge influence range is, the larger the width of the topological edge of the map is. Wherein the topological edge influence range can also be used for determining the number of lanes in the topological edge of the map. The method comprises the following steps: dividing the topological edge influence range by a preset single-lane influence range to obtain the number of lanes; and rounding down the number of lanes to obtain the number of target lanes. The preset single-lane influence range can be set according to actual conditions, and the invention is not particularly limited to the actual conditions.
For example, if the preset single-lane influence range is 50 cm and the topological edge influence range is 180 cm, dividing the topological edge influence range 180 by the preset single-lane influence range 50 to obtain the number of lanes 3.6, and rounding down the number of lanes 3.6 to obtain the number of target lanes 3.
In an embodiment, topology edges are constructed in the map according to at least one parameter of the topology direction, the topology edge influence range and the length of the map topology edges, and map topology edges are generated.
And step S1012, carrying out fusion association on the map grids and the topological points with the same coordinates to generate the target map.
Wherein the target map comprises a map grid and map topological edges.
In one embodiment, coordinates of each map grid and coordinates of each topological point in each map topological edge are obtained; and carrying out fusion association on the map grids and the topological points with the same coordinates to generate the target map. By fusion-associating the map grids and topological points with the same coordinates, the target map can be accurately generated.
Specifically, the first map in fig. 4 is marked in a rectangular coordinate system, the second map in fig. 5 is marked in a rectangular coordinate system, coordinates of each map grid in the first map are obtained, coordinates of each topological point in a map topological edge in the second map are obtained, the map grids with the same coordinates are associated with the topological points, and the first map and the second map are fused to obtain the target map.
And step S102, planning a navigation path in the target map based on the navigation task to obtain a candidate navigation path.
The candidate navigation path is a navigation path capable of reaching an end point from a start point.
In an embodiment, as shown in fig. 7, fig. 7 is a schematic flow chart of sub-steps of step S102 of the navigation path planning method in fig. 1, and step S102 includes sub-steps S1021 to S1022.
And step S1021, starting from the initial point, performing path extension according to a preset path searching rule until reaching the end point of the navigation task.
Searching a starting point of a navigation task in a target map, and starting from the starting point, performing path extension according to a preset path searching rule until reaching the end point of the navigation task. The preset path searching rule is to prioritize the path extension of the map topological edge, and the path extension is carried out by the map grid under the condition that the map topological edge is not searched. By performing path extension at the start point and the end point of the navigation task, each extension path can be accurately obtained.
In an embodiment, searching a starting point of a navigation task in a target map, taking a map grid where the starting point is located as a starting point of a candidate navigation path when the starting point is not coincident with a map topology edge, searching the navigation path in a preset navigation searching mode, and taking a connected map topology edge as an extension path and extending the path when the connected map topology edge extends to the map topology edge; under the condition that the next section of map topological edge exists at the tail end of the map topological edge, taking the next section of map topological edge as an extension path and carrying out path extension; and under the condition that the tail end of the topological path does not exist in the next section of map topological edge, carrying out grid path extension on the path extension tail end in the map grid until the navigation task is ended, and obtaining each extension path in the path extension process.
In an embodiment, searching a starting point of a navigation task in a target map, taking a map topology edge where the starting point is located as a starting point of a candidate navigation path under the condition that the starting point coincides with a map topology edge, searching the navigation path in a preset navigation searching mode, taking the next section of map topology edge as an extension path under the condition that the next section of map topology edge exists at the tail end of the map topology edge, and carrying out path extension; and under the condition that the tail end of the map topological edge does not exist in the next section of map topological edge, taking the map grid where the path extending tail end is positioned as an extending path and carrying out path extension until the navigation task is ended, and obtaining each extending path in the path extension process.
It should be noted that the preset navigation search mode may be set according to actual situations, which is not limited in the embodiment of the present invention, for example, the preset navigation search mode may be an a-type algorithm or a D-type algorithm.
And step 1022, obtaining each extension path in the navigation path search, and splicing the extension paths to obtain the candidate navigation path.
And acquiring each extension path in the navigation path search to obtain a plurality of extension paths, and splicing the extension paths according to the time sequence of the navigation path search to obtain candidate navigation paths. By splicing the extension paths, the candidate navigation paths can be accurately obtained, and the efficiency and accuracy of navigation path planning are greatly improved.
Step S103, acquiring the grid distance and the topological distance of the candidate navigation path in the target map.
The grid distance is the navigation path length of the map grid path, and the topological distance is the navigation path length of the map topological edge path.
In an embodiment, as shown in fig. 8, fig. 8 is a schematic flow chart of sub-steps of step S103 of the navigation path planning method in fig. 1, and step S103 includes sub-steps S1031 to S1033.
And step S1031, obtaining the grid number of the map grids related to the candidate navigation paths.
And acquiring the grid number of the map grids in the candidate navigation path to obtain the grid number of the candidate navigation path. By counting the number of grids of the map grids related to the candidate navigation path, the accuracy of navigation path planning can be improved.
As shown in fig. 9, fig. 9 is a schematic diagram of another scenario for implementing the navigation path planning method provided in the present embodiment, and if the number of grids of the map grid 51 in fig. 9 is 19, the number of grids of the map grid is determined to be 19.
In an embodiment, the grid number includes a first grid number of extension points of the map grid extending to an area of influence of the map topology edge; and a second grid number extending points to the map topology edge. Obtaining the grid number of extension points of each map grid extending to the matched map topological edge influence range in the candidate navigation path, and obtaining a first grid number; obtaining the grid number from each extension point to the matched map topological edge, and obtaining a second grid number; and superposing the first grid number and the second grid number to obtain the grid number of the map grids related to the candidate navigation path. By superposing the first grid number of the map grids extending to the extending points and the second grid number of the extending points to the map topological edge, the grid number of the map grids can be accurately obtained.
As shown in fig. 10, fig. 10 is a schematic diagram of another scenario for implementing the navigation path planning method provided in this embodiment, where in fig. 10, a connection extending point of the map grid 10 and the influence range 21 of the map topological side 20 is M, the number of grids of the map grid segment a extending from the map grid 10 to the extending point M is obtained, the first number of grids is obtained, the number of grids of the map grid segment b extending from the extending point M to the matched map topological side 20 is obtained, and the second number of grids is obtained, which is 1. And superposing the first grid number 5 and the second grid number 1 to obtain the grid number 6 of the map grids related to the candidate navigation path.
And S1032, determining the grid distance of the candidate navigation path in the target map according to the grid number and the preset grid unit length.
The preset grid unit length is a ratio of a preset map grid to an actual length, and may be set according to practical situations, which is not particularly limited in the embodiment of the present invention, for example, the preset grid unit length may be set to 0.5 meters.
For example, the number of grids is 30, and the preset grid unit length may be set to 0.5 meters, the grid distance of the candidate navigation path in the target map is 1.5 meters. For another example, the number of grids is 50, and the preset grid unit length may be set to 1 meter, and then the grid distance of the candidate navigation path in the target map is 50 meters.
And step S1033, obtaining the projection length of the candidate navigation path on the map topological edge, and determining the projection length as the topological distance in the target map.
As shown in fig. 11, fig. 11 is a schematic diagram of another scenario for implementing the navigation path planning method provided in the present embodiment, where the candidate navigation path a passes through the map topology edge 20, the projection of the candidate navigation path a in the map topology edge influence range 21 on the map topology edge 20 is denoted as C, and the projection C is determined as the topology distance in the target map.
Step S104, determining the cost value of the candidate navigation path according to the grid distance and the topology distance of the candidate navigation path.
The cost value is used for representing a cost value required by the mobile robot to run on the candidate navigation path, and the smaller the cost value is, the better the candidate navigation path is.
In one embodiment, performing multiplication operation on the grid distance of the candidate navigation path and a preset grid weight parameter to obtain a grid cost value; multiplying the topology distance of the candidate navigation path and a preset topology weight parameter to obtain a topology cost value, wherein the preset grid weight parameter is larger than the preset topology weight parameter; and carrying out addition operation on the grid cost value and the topology cost value to obtain the cost value of the candidate navigation path. The preset grid weight parameter and the preset topology weight parameter may be set according to actual situations, which is not limited in the embodiment of the present invention, for example, the preset grid weight parameter may be set to 0.9, and the preset topology weight parameter may be set to 0.1. By setting different preset grid weight parameters and preset topology weight parameters, the type of the navigation path preferential selection can be set, and the efficiency and accuracy of navigation path planning are greatly improved.
For example, the preset grid weight parameter is 0.9 and the preset topology weight parameter is 0.1; the grid distance of the candidate navigation path is 20 meters, the topology distance of the candidate navigation path is 10 meters, and the preset grid weight parameter 0.9 and the grid distance 20 are multiplied to obtain the grid cost value of 18; multiplying a preset topology weight parameter 0.1 and a topology distance 10 to obtain a topology cost value of 1; and (3) carrying out addition operation on the grid cost value 18 and the topology cost value 1 to obtain the cost value 19 of the candidate navigation path.
It should be noted that, by setting the preset grid weight parameter and the preset topology weight parameter that are different, a required navigation map type (grid navigation type or topology edge navigation type) can be preferably selected when planning the navigation path. The navigation map type with smaller weight parameters has higher priority; that is, in the case that the priority of the topology edge navigation type is greater than that of the grid navigation type, the preset grid weight parameter is greater than the preset topology weight parameter. And under the condition that the priority of the topological edge navigation type is smaller than that of the grid navigation type, the preset grid weight parameter is smaller than the preset topological weight parameter. By setting different preset grid weight parameters and preset topology weight parameters, the topology edge of the running map of the mobile robot can be planned preferentially, the running path is optimized, the safety is improved, and the path optimization cost is reduced.
Step S105, determining a target navigation path from the candidate navigation paths according to the cost value of the candidate navigation paths.
And after obtaining the cost value of each candidate navigation path, determining the candidate navigation path with the minimum cost value as the target navigation path. The most suitable target navigation path can be accurately determined according to the cost value, and the efficiency and accuracy of navigation path planning are greatly improved.
For example, the cost value of the candidate navigation path 1 is 10, the cost value of the candidate navigation path 2 is 50, the cost value of the candidate navigation path 3 is 8, the cost value of the candidate navigation path 4 is 22, the cost value of the candidate navigation path 5 is 15, the cost value 8 of the candidate navigation path 3 is minimum, and the candidate navigation path 3 is determined as the target navigation path.
In one embodiment, after the target navigation path is obtained, the target navigation path is smoothed to generate an updated target navigation path. By performing smoothing processing on the target navigation path, the smoothness of robot operation can be improved. The smoothing method may be selected according to practical situations, which is not limited in the embodiment of the present invention. For example, the smoothing process may be a cubic spline interpolation process.
According to the navigation path planning method provided by the embodiment, the target map fused with the map grid and the map topological edge is obtained, and the target map is used for carrying out hybrid navigation path planning, so that the path can be customized, and the obstacle avoidance purpose can be achieved. The cost value of the candidate navigation path can be accurately determined according to the grid distance and the topological distance of the candidate navigation path, and the safer and more reliable target navigation path can be accurately determined from the candidate navigation path according to the cost value of the candidate navigation path, so that the reliability and the controllability of navigation path planning are greatly improved.
Referring to fig. 12, fig. 12 is a schematic block diagram of a structure of a terminal device according to an embodiment of the present application.
As shown in fig. 12, the terminal device 200 includes a processor 202 and a memory 203 connected through a system bus 201, wherein the memory 203 may include a storage medium and an internal memory.
The storage medium may store a computer program. The computer program comprises program instructions which, when executed, cause the processor to perform any one of a number of navigation path planning methods.
The processor 202 is used to provide computing and control capabilities to support the operation of the overall terminal device.
The internal memory provides an environment for the execution of a computer program in a storage medium that, when executed by a processor, causes the processor to perform any one of the navigation path planning methods.
It will be appreciated by those skilled in the art that the structure shown in fig. 12 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the terminal device to which the present application is applied, and that a particular terminal device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
It should be appreciated that the processor 202 may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Wherein in one embodiment, the processor 202 is configured to execute a computer program stored in a memory to implement the steps of:
acquiring a target map and a navigation task, wherein the target map comprises a map grid and map topological edges;
planning a navigation path in the target map based on the navigation task to obtain a candidate navigation path;
acquiring grid distance and topology distance of the candidate navigation path in the target map;
determining a cost value of the candidate navigation path according to the grid distance and the topology distance of the candidate navigation path;
and determining a target navigation path from the candidate navigation paths according to the cost value of the candidate navigation paths.
In one embodiment, the processor 202, when implementing the obtaining the grid distance and the topology distance of the candidate navigation paths in the target map, is configured to implement:
acquiring the grid number of map grids related to the candidate navigation paths;
determining the grid distance of the candidate navigation path in the target map according to the grid number and the preset grid unit length;
and acquiring the projection length of the candidate navigation path on the topological edge of the map, and determining the projection length as the topological distance in the target map.
In one embodiment, the grid number includes a first grid number of extension points of a map grid extending to an area of influence of the map topology edge; and a second grid number extending from the point to the map topology edge.
In one embodiment, the processor 202, when implementing the number of grids of the map grid involved in acquiring the candidate navigation paths, is configured to implement:
obtaining the grid number of extension points of each map grid extending to the matched map topological edge influence range in the candidate navigation path, and obtaining the first grid number;
obtaining the grid number from each extension point to the matched map topological edge, and obtaining the second grid number;
and superposing the first grid number and the second grid number to obtain the grid number of the map grids related to the candidate navigation path.
In one embodiment, when implementing the determining the cost value of the candidate navigation path according to the grid distance and the topology distance of the candidate navigation path, the processor 202 is configured to implement:
multiplying the grid distance of the candidate navigation path and a preset grid weight parameter to obtain a grid cost value;
multiplying the topology distance of the candidate navigation path and a preset topology weight parameter to obtain a topology cost value, wherein the preset grid weight parameter is larger than the preset topology weight parameter;
and carrying out addition operation on the grid cost value and the topology cost value to obtain the cost value of the candidate navigation path.
In one embodiment, when implementing the navigation path planning in the target map based on the navigation task, the processor 202 is configured to implement:
starting from the initial point, carrying out path extension according to a preset path searching rule until reaching the end point of the navigation task;
obtaining each extension path in the navigation path search, and splicing the extension paths to obtain the candidate navigation path;
the preset path searching rule is to prioritize the path extension of the map topological edge, and the path extension is carried out by the map grid under the condition that the map topological edge is not searched.
In one embodiment, the processor 202, when implementing the acquisition target map, is configured to implement:
acquiring map topological edges and map grids, and acquiring coordinates of each map grid and coordinates of each topological point in each map topological edge;
and carrying out fusion association on the map grids and the topological points with the same coordinates to generate the target map.
In one embodiment, the processor 202, when implementing the acquiring map topology edges, is configured to implement:
obtaining topological attributes of each map topological edge to be built, wherein the topological attributes at least comprise a topological direction and a topological edge influence range;
and constructing map topology edges in the middle of the map according to the topology attribute of each map topology edge to be constructed, and generating the map topology edges.
In one embodiment, the topological attribute comprises a topological direction, the topological direction comprising unidirectional and bidirectional;
if the topological distance is set to be a limit value, determining that the topological direction is unidirectional;
and if the topological distance is not set to be the limit value, determining that the topological direction is bidirectional.
In one embodiment, when implementing the map association between the map grid and the map topology edge, the processor 202 is configured to implement:
acquiring coordinates of each map grid and coordinates of each topological point in each map topological edge;
and carrying out fusion association on the map grids and the topological points with the same coordinates to generate the target map.
It should be noted that, for convenience and brevity of description, the specific working process of the terminal device described above may refer to the corresponding process in the foregoing navigation path planning method embodiment, which is not described herein again.
Embodiments of the present application also provide a computer readable storage medium having a computer program stored thereon, where the computer program includes program instructions, and when the program instructions are executed, the method implemented by the method may refer to various embodiments of the navigation path planning method of the present application.
The computer readable storage medium may be an internal storage unit of the terminal device according to the foregoing embodiment, for example, a hard disk or a memory of the terminal device. The computer readable storage medium may be nonvolatile or may be volatile. The computer readable storage medium may also be an external storage device of the terminal device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device.
It is to be understood that the terminology used in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should also be understood that the term "and/or" as used in this specification refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present application are merely for describing, and do not represent advantages or disadvantages of the embodiments. While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the invention.
Claims (11)
1. A navigation path planning method, comprising:
acquiring a target map and a navigation task, wherein the target map comprises a map grid and map topological edges;
planning a navigation path in the target map based on the navigation task to obtain a candidate navigation path;
acquiring grid distance and topology distance of the candidate navigation path in the target map;
determining a cost value of the candidate navigation path according to the grid distance and the topology distance of the candidate navigation path;
and determining a target navigation path from the candidate navigation paths according to the cost value of the candidate navigation paths.
2. The navigation path planning method of claim 1, wherein the obtaining the grid distance and the topology distance of the candidate navigation path in the target map comprises:
acquiring the grid number of map grids related to the candidate navigation paths;
determining the grid distance of the candidate navigation path in the target map according to the grid number and the preset grid unit length;
and acquiring the projection length of the candidate navigation path on the topological edge of the map, and determining the projection length as the topological distance in the target map.
3. The navigation path planning method of claim 2, wherein the grid number comprises a first grid number of extension points of a map grid extending to an area of influence of the map topological edge; and a second grid number extending from the point to the map topology edge.
4. A navigation path planning method according to claim 3 wherein the obtaining the number of grids of the map grids to which the candidate navigation path relates comprises:
obtaining the grid number of extension points of each map grid extending to the matched map topological edge influence range in the candidate navigation path, and obtaining the first grid number;
obtaining the grid number from each extension point to the matched map topological edge, and obtaining the second grid number;
and superposing the first grid number and the second grid number to obtain the grid number of the map grids related to the candidate navigation path.
5. The navigation path planning method of claim 1, wherein the determining the cost value of the candidate navigation path based on the grid distance and the topology distance of the candidate navigation path comprises:
multiplying the grid distance of the candidate navigation path and a preset grid weight parameter to obtain a grid cost value;
multiplying the topology distance of the candidate navigation path and a preset topology weight parameter to obtain a topology cost value, wherein the preset grid weight parameter is larger than the preset topology weight parameter;
and carrying out addition operation on the grid cost value and the topology cost value to obtain the cost value of the candidate navigation path.
6. The navigation path planning method according to claim 1, wherein the performing navigation path planning in the target map based on the navigation task to obtain candidate navigation paths includes:
starting from the initial point, carrying out path extension according to a preset path searching rule until reaching the end point of the navigation task;
obtaining each extension path in the navigation path search, and splicing the extension paths to obtain the candidate navigation path;
the preset path searching rule is to prioritize the path extension of the map topological edge, and the path extension is carried out by the map grid under the condition that the map topological edge is not searched.
7. The navigation path planning method according to claim 1, wherein the acquiring the target map includes:
acquiring map topological edges and map grids, and acquiring coordinates of each map grid and coordinates of each topological point in each map topological edge;
and carrying out fusion association on the map grids and the topological points with the same coordinates to generate the target map.
8. The navigation path planning method of claim 7 wherein the obtaining map topology edges comprises:
obtaining topological attributes of each map topological edge to be built, wherein the topological attributes at least comprise a topological direction and a topological edge influence range;
and constructing map topological edges in the map according to the topological attribute of each map topological edge to be constructed, and generating the map topological edges.
9. The navigation path planning method of claim 8 wherein the topological attribute comprises a topological direction, the topological direction comprising unidirectional and bidirectional;
if the topological distance is set to be a limit value, determining that the topological direction is unidirectional;
and if the topological distance is not set to be the limit value, determining that the topological direction is bidirectional.
10. A terminal device, characterized in that the terminal device comprises a processor, a memory, and a computer program stored on the memory and executable by the processor, wherein the computer program, when executed by the processor, realizes the steps of the navigation path planning method according to any of claims 1 to 9.
11. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program, wherein the computer program, when executed by a processor, implements the steps of the navigation path planning method according to any of claims 1 to 9.
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