CN112432652A - Route planning system and route planning method - Google Patents
Route planning system and route planning method Download PDFInfo
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- CN112432652A CN112432652A CN202110100236.2A CN202110100236A CN112432652A CN 112432652 A CN112432652 A CN 112432652A CN 202110100236 A CN202110100236 A CN 202110100236A CN 112432652 A CN112432652 A CN 112432652A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/343—Calculating itineraries, i.e. routes leading from a starting point to a series of categorical destinations using a global route restraint, round trips, touristic trips
Abstract
The invention relates to a path planning system and a path planning method, which belong to the technical field of robot navigation, wherein the path planning system comprises at least two levels of planners, and the planning range of each level of planners is different; the first-stage planner is responsible for planning from the starting point to the end point; the other levels of planners are responsible for planning from the starting point to respective planning ranges, and the planning precision and the planning frequency of the planners are in inverse proportion to the planning ranges; the path planning method comprises the steps of taking a path planned by each stage of planner, and solving the difference of the planned paths of two adjacent stages of planners to obtain a segmented path; and solving and integrating the segmented path and the planned path of the planner with the highest progression to obtain a final path. According to the actual requirement of the robot navigation, the invention reduces the unnecessary consumption of the remote planning of the robot, not only can obtain an effective and stable path, enhance the reaction capability of the robot in the navigation, enhance the real-time performance of the robot navigation, improve the reaction speed to real-time obstacles, but also can reduce the resource waste in the planning.
Description
Technical Field
The invention relates to the technical field of robot navigation, in particular to a path planning system and a path planning method.
Background
The existing path planning algorithm mainly comprises: dijkstra algorithm, a algorithm, D path search algorithm, PRM, RRT path planning algorithm, and artificial potential field method.
Dijkstra's algorithm is an earlier path planning algorithm, and is a classic breadth-first state space search algorithm, i.e., the algorithm searches the entire free space layer by layer from an initial point until reaching a target point. The Dijkstra algorithm makes many useless calculations during the planning process.
The A-star algorithm adds a heuristic method on the basis of Dijkstra, and reduces a large amount of unnecessary searches. The a-algorithm has been widely used in mobile robot navigation. A, although unnecessary search amount in the planning process is effectively reduced, the requirements of robot navigation in different ranges on paths are still not distinguished, resource waste is caused, and the planning frequency is difficult to improve.
The path search algorithm is a heuristic path search algorithm and is suitable for scenes with unknown surrounding environment or dynamically changing surrounding environment. The path searching algorithm adopts a mode similar to that equipotential lines are expanded step by step during off-line path planning, and map nodes are traversed from target points, so that the searching range is large, the searching efficiency is low, and the problem is more prominent particularly when the searching map area is large.
The PRM is a method based on graph search, which randomly sets road sign points in space, performs collision detection, and searches for a path on a road graph by utilizing search algorithms such as A-x and the like. When a narrow passage exists in a planning environment, the PRM algorithm is difficult to plan successfully and has insufficient stability.
The RRT path planning algorithm is a method for continuously growing a random tree in a planning space, and can rapidly complete planning in a complex space by rapidly expanding the random tree in a random direction. However, the RRT has a random tree growth direction in the expansion process, which results in low algorithm search efficiency and low convergence rate; in addition, in a dynamic environment, the results of each planning may be different, and a stable path cannot be formed;
the artificial potential field method is a method for artificially creating a potential field, and the robot is enabled to avoid obstacles and reach a target point under the guidance of potential difference by respectively adding the actions of repelling and attracting the robot to the obstacles and the target point. The artificial potential field method may trap into a local minimum trap under individual conditions, which may result in failure to complete a planning task and instability.
The existing path planning algorithms have common defects: the planning range is not distinguished during planning, and planning is carried out with the same precision, so that unnecessary calculation is caused, and the planning frequency is reduced. The method is not suitable for large-scale planning or scenes with large calculation amount such as three-dimensional space.
Disclosure of Invention
The present invention provides a path planning system and a path planning method for solving the above problems.
The invention is realized by the following technical scheme:
the path planning system comprises at least two levels of planners, the planning range of each level of planners is different, and the planning precision and the planning frequency of the planners are in inverse proportion to the planning range.
Further, the system comprises three levels of planners, which are respectively:
a first-stage planner: planning from the starting point to the end point;
a second-stage planner: planning a second planning range, wherein the second planning range is smaller than the range from the starting point to the end point;
a third-level planner: and planning a third planning range, wherein the third planning range is smaller than the second planning range.
Preferably, the second planned range is greater than the sensor monitoring range.
The path planning method adopts the path planning system to plan the path, the higher the level number of the planner is, the smaller the planning range is, and the planner of each level starts to plan from the starting point;
taking the path planned by each level of planner, and solving the difference of the planned paths of two adjacent levels of planners to obtain a segmented path;
and solving and integrating the segmented path and the planned path of the planner with the highest progression to obtain a final path.
Furthermore, each level of planner has respective threads, and is controlled and started by a flag bit; this flag will be true when the target coordinates are entered; when the mark is true, the thread starts working; otherwise the thread enters a sleep state.
Further, the targets of the next-level planner are derived from the path of the previous-level planner.
Further, the planning process of the first path is as follows:
judging whether the distance between the robot and the terminal is smaller than a first threshold value or not, and if so, enabling the first-stage planner to enter a sleep mode; if not, starting the first-stage planner to generate a first path.
Further, the planning process of the second path is as follows:
judging whether the distance between the robot and a target point of the second-stage planner is smaller than a second threshold value, if so, enabling the second-stage planner to enter a sleep mode; if not, judging the distance between the robot and the total target point:
when the distance between the robot and the total target point is larger than the planning range of a second-level planner, setting the point of the first path, the distance of which is the range of the second-level planner, as the target point of the second-level planner;
when the distance between the robot and the total target point is smaller than the range of the second-level planner, setting the total target point as the target point of the second-level planner;
after the target point setting of the second-stage planner is finished, starting the second-stage planner to generate a second path;
if the first path is not generated, entering a circular dormancy waiting state; the second threshold value is less than the first threshold value.
Further, the planning process of the third path is as follows:
judging whether the distance between the robot and a target point of the third-level planner is smaller than a third threshold value, if so, enabling the third-level planner to enter a sleep state; if not, judging the distance between the robot and the total target point:
when the distance between the robot and the total target point is larger than the planning range of a third-level planner, setting the point on the second path, the distance of which is the range of the third-level planner, as the target point of the third-level planner;
when the distance between the robot and the total target point is smaller than the range of the third-level planner, setting the total target point as the target point of the third-level planner;
after the target point setting of the third-level planner is finished, starting the third-level planner to generate a third path;
if the second path is not generated, entering a circular dormancy waiting state; the third threshold is less than the second threshold.
Preferably, the first threshold is a planning distance of a second-level planner; the second threshold is the planning distance of the third level planner.
Compared with the prior art, the invention has the following beneficial effects:
according to the actual requirement of the robot navigation, the invention reduces the unnecessary consumption of the remote planning of the robot, not only can obtain an effective and stable path, enhance the reaction capability of the robot in the navigation, enhance the real-time performance of the robot navigation, improve the reaction speed to real-time obstacles, but also can reduce the resource waste in the planning.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention.
FIG. 1 is a graph of the search volume under A in a first obstacle;
FIG. 2 is a graph of the search volume for A under a second obstacle;
FIG. 3 is a flow chart of the first embodiment;
FIG. 4 is a diagram of the effects of path planning by a three-level planner;
fig. 5 is a schematic diagram of the combination of three paths into a final path.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
In order to allow the quadruped robot to complete a navigation task and simultaneously achieve excellent motion capability to complete tasks such as going up and down stairs, it is necessary to plan a three-dimensional path in a three-dimensional space, and the computation amount is much larger than that in a two-dimensional plane. However, the navigation system has high requirements for real-time performance, so that the path planning must reach a certain operation speed.
For the a-algorithm, the more nodes that need to be traversed when planning a path takes the more time, so it is desirable to have as few nodes as possible. Generally, when the map resolution is constant, the farther the set target point is from the starting point, the more nodes need to be traversed. As the terrain becomes more complex, the more nodes that need to be traversed. And the farther away the distance, the more complex the terrain is, as shown in fig. 1 and 2, the black part is an obstacle and the red part is a traversed node.
However, the target point is of course not modifiable, so the method of reducing the amount of planning may be to reduce the map accuracy in turn to reduce the amount of search. But the consequence of this is that the path accuracy as a guide for the robot movement is not sufficient, resulting in a high probability that the robot will hit an obstacle. A certain accuracy of the planning is necessary, while also the speed of the planning is necessary. But these are difficult to implement on a single planning line.
Although it is desirable that the robot follow a precise path, the robot should not react too precisely to terrain or obstacles at large distances, which is not helpful for the navigation of the robot. Therefore, only the path in a close range to the robot needs to be accurate, and the path in a long range only needs to be roughly provided. Secondly, due to the limited sensor range, the robot cannot know the obstacle exceeding the sensor range. Therefore, the path not within the range of the robot sensor does not need to be updated quickly, and the distance from the target point to the boundary of the range of the robot sensor usually occupies most of the entire path, and the quick update consumes a lot of calculation power.
In general, it is desirable to plan a path at a short distance with high frequency and high precision, and vice versa at a long distance.
Through the thought, the path planning system disclosed by the invention comprises at least two levels of planners, the planning range of each level of planners is different, and the planning precision and the planning frequency of the planners are inversely proportional to the planning range.
The planner employs the existing path planning algorithm for path planning, which is conventional in the art and will not be described herein.
The path planning method disclosed by the invention adopts the path planning system to plan the path, and the higher the level number of the planner is, the smaller the planning range is;
planning from the starting point by each level of planner, taking the path planned by each level of planner, and solving the difference of the planned paths of two adjacent levels of planners to obtain a segmented path; and solving and integrating the segmented path and the planned path of the planner with the highest progression to obtain a final path.
Each stage of the planner has a respective thread and does not work serially. Each level of planner is controlled to start through a mark; the mark is set to be true when the target coordinate is input, the thread starts to work when the mark is set to be true, and otherwise, the thread enters a dormant state.
Based on the path planning system, the invention discloses an embodiment.
Example 1
In this embodiment, the planner is divided into three stages, namely a first stage planner, a second stage planner and a third stage planner. The planning precision and the planning frequency of the first-stage planner are smaller than those of the second-stage planner, and the planning precision and the planning frequency of the second-stage planner are smaller than those of the third-stage planner.
A first-stage planner: and planning from the starting point to the end point. The planning speed is increased by reducing the planning precision, but the planning does not require very high frequency, namely, the planning has larger breadth and lower precision and speed.
A second-stage planner: is responsible for planning from the starting point to a range greater than the sensor. Due to the fact that the range of the sensor is exceeded, the situation that the target cannot be reached is avoided. The second-stage planner plays a role in quickly avoiding obstacles, and has higher speed and general precision. It provides smooth planning conditions for the third-level planner; the target of the second-level planner is then the path from the first-level planner.
A third-level planner: the robot can be planned only within the range from the starting point to one meter, so that the planning precision and the planning speed are high, and the robot can accurately and quickly avoid obstacles. The target of the third-level planner is derived from the path of the second-level planner.
As shown in fig. 3, the three-level planner is divided into three threads.
And in the constructor of the first-stage planner, setting the resolution of the A-x planner to be higher according to the requirement.
The main process of planning the path by the first-stage planner is as follows: setting a starting flag amount Goal _ Reach for the whole planner and setting false initially, wherein the flag is set to be true when a target coordinate is input, and starting working; otherwise, the thread enters a dormant state to avoid occupying resources.
After the robot starts working, firstly updating the coordinates of the current robot, judging whether the distance between the robot and the terminal is smaller than a first threshold value, if so, clearing the path and entering dormancy;
if not, updating a local map (the global map is loaded when the system is started), obtaining real-time point clouds, obtaining the point clouds with the same resolution as the planner through voxel filtering, converting the point clouds into a map for navigation, and colliding the map for the A-star planner to use;
and then starting an A-x planner to find a path, and scaling the returned path according to the resolution to obtain path points under an actual world coordinate system to generate a first path.
The first threshold is set according to needs, in the embodiment, the first threshold is the planning distance of the second-stage planner, and the second-stage planner is responsible for path planning within a range of 3 meters, so that the first threshold is 3 meters; when the coordinates of the robot reach the range of the target point within 3 meters, the first-stage planner enters the dormancy.
In order to control the working frequency of the planner, the planner does not need to occupy the computer resources meaninglessly, calculates the time spent by the thread function, and sets the working frequency to enable the residual time of the thread to enter the sleep state so as to avoid occupying other thread resources.
The second-level planner is substantially the same as the first-level planner, except that the parameters are different, the second-level planner determines the distance between the current coordinates of the robot and the total target point when setting the target. The main process is as follows:
after the robot starts to work, judging whether the distance between the robot and a target point of the second-stage planner is smaller than a second threshold value or not, if so, enabling the second-stage planner to enter a sleep state; if not, judging the distance between the current coordinate of the robot and the total target point:
when the distance between the robot and the total target point is larger than the planning range of a second-level planner, setting the point of the first path, the distance of which is the range of the second-level planner, as the target point of the second-level planner; if the first path is not generated, entering a circular dormancy waiting state;
when the distance between the robot and the total target point is smaller than the range of the second-level planner, setting the total target point as the target point of the second-level planner;
and after the target point setting of the second-level planner is finished, starting the second-level planner to generate a second path.
The second threshold is set as desired, but should be less than the first threshold. In this embodiment, the second threshold is a planning distance of a third-level planner, and the third-level planner is responsible for path planning within a range of 1 meter, so the second threshold is 1 meter; and when the coordinates of the robot reach the range of the target point within 1 meter, the second-level planner enters the dormancy.
The third level planner is essentially the same as the second level planner, but the third level planner also takes on the role of completing the entire planning task. And after the third-level planner judges that the robot has reached the target point range, setting the starting flag amount Goal _ Reach of the whole planner to be false, and stopping the whole planning system.
The main process of planning the path by the third-level planner is as follows: judging whether the distance between the robot and a target point of the third-level planner is smaller than a third threshold value, if so, enabling the third-level planner to enter a sleep state; if not, judging the distance between the current coordinate of the robot and the total target point:
when the distance between the robot and the total target point is larger than the planning range of a third-level planner, setting the point on the second path, the distance of which is the range of the third-level planner, as the target point of the third-level planner; if the second path is not generated, entering a circular dormancy waiting state;
when the distance between the robot and the total target point is smaller than the range of the third-level planner, setting the total target point as the target point of the third-level planner;
and after the target point setting of the third-level planner is finished, starting the third-level planner to generate a third path.
The third threshold value should be smaller than the second threshold value, and the third threshold value can be reasonably set according to factors such as planning precision and efficiency of the third-level planner.
As shown in fig. 4 and 5, the three paths returned by the three planners are the first path planned by the first-stage planners, the second path planned by the second-stage planners and the third path planned by the third-stage planners.
And taking the third path as a first section of path, taking the rest part of the second path, which is removed from the part overlapped with the third path, as a second section of path, and taking the rest part of the first path, which is removed from the part overlapped with the second path, as a third section of path.
Then, the first path section I, the second path section II and the third path section III are combined to form a final path, so that a path close to the robot part is obtained, and the planning frequency and the planning precision are high; and a path which consumes less resources at a part far away from the robot and has quick overall obstacle avoidance response is provided.
According to the actual requirement of the robot navigation, the invention reduces the unnecessary consumption of the remote planning of the robot, not only can obtain an effective and stable path, enhance the reaction capability of the robot in the navigation, enhance the real-time performance of the robot navigation, improve the reaction speed to real-time obstacles, but also can reduce the resource waste in the planning.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. The path planning system is characterized in that: the planning range of each stage of the planner is different, and the planning precision and the planning frequency of the planner are in inverse proportion to the planning range.
2. The path planning system according to claim 1, characterized in that: the three-level planner is included, which is respectively:
a first-stage planner: planning from the starting point to the end point;
a second-stage planner: planning a second planning range, wherein the second planning range is smaller than the range from the starting point to the end point;
a third-level planner: and planning a third planning range, wherein the third planning range is smaller than the second planning range.
3. The path planning system according to claim 2, characterized in that: the second planned range is greater than the sensor monitoring range.
4. The path planning method is characterized by comprising the following steps: the path planning system of any one of claims 1-3 is adopted to plan a path, the higher the number of stages of planners is, the smaller the planning range is, and each stage of planners starts to plan from a starting point;
taking the path planned by each level of planner, and solving the difference of the planned paths of two adjacent levels of planners to obtain a segmented path;
and solving and integrating the segmented path and the planned path of the planner with the highest progression to obtain a final path.
5. The path planning method according to claim 4, characterized in that: each level of planner has respective thread, and each level of planner is controlled to be started through a mark; this flag will be true when the target coordinates are entered; when the mark is true, the thread starts working; otherwise the thread enters a sleep state.
6. The path planning method according to claim 5, characterized in that: the targets for the next-level planner are derived from the path of the previous-level planner.
7. The path planning method according to claim 6, characterized in that: the planning process of the first path is as follows:
judging whether the distance between the robot and the terminal is smaller than a first threshold value or not, and if so, enabling the first-stage planner to enter a sleep mode; if not, starting the first-stage planner to generate a first path.
8. The path planning method according to claim 7, characterized in that: the planning process of the second path is as follows:
judging whether the distance between the robot and a target point of the second-stage planner is smaller than a second threshold value, if so, enabling the second-stage planner to enter a sleep mode; if not, judging the distance between the robot and the total target point:
when the distance between the robot and the total target point is larger than the planning range of a second-level planner, setting the point of the first path, the distance of which is the range of the second-level planner, as the target point of the second-level planner;
when the distance between the robot and the total target point is smaller than the range of the second-level planner, setting the total target point as the target point of the second-level planner;
after the target point setting of the second-stage planner is finished, starting the second-stage planner to generate a second path;
if the first path is not generated, entering a circular dormancy waiting state; the second threshold value is less than the first threshold value.
9. The path planning method according to claim 8, characterized in that: the planning process of the third path is as follows:
judging whether the distance between the robot and a target point of the third-level planner is smaller than a third threshold value, if so, enabling the third-level planner to enter a sleep state; if not, judging the distance between the robot and the total target point:
when the distance between the robot and the total target point is larger than the planning range of a third-level planner, setting the point on the second path, the distance of which is the range of the third-level planner, as the target point of the third-level planner;
when the distance between the robot and the total target point is smaller than the range of the third-level planner, setting the total target point as the target point of the third-level planner;
after the target point setting of the third-level planner is finished, starting the third-level planner to generate a third path;
if the second path is not generated, entering a circular dormancy waiting state; the third threshold is less than the second threshold.
10. The path planning method according to any one of claims 9, characterized in that: the first threshold value is the planning distance of the second-stage planner; the second threshold is the planning distance of the third level planner.
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