Three-dimensional space multi-target path planning method combining RRT algorithm and ant colony algorithm

Abstract

The invention discloses a three-dimensional space multi-target path planning method combining an RRT algorithm and an ant colony algorithm. According to the method, a linear line distance between target points is used as an initial path cost, a multi-target path planning problem in a three-dimensional space is converted into a travelling salesman problem with a known path cost, then optimization solution is performed on the travelling salesman problem by using the ant colony algorithm, the passing times of ants on the path between the target points and the optimal solution in each iteration are recorded in the optimization process, if the passing times of ants of the path between two target points exceed a threshold, or the path is contained in the optimal solution of certain iteration, the three-dimensional space path between the two target points is planned by using the RRT algorithm, the initial path cost between the two target points is replaced with the planned path distance, andafter a certain number of iterations, a three-dimensional space path that returns to the starting point after passing by all target points and has a total path cost tending to be minimized can be found.

Description

technical field [0001] The invention relates to a three-dimensional space multi-objective path planning method which combines RRT and ant colony algorithm, and belongs to the field of robot path planning. Background technique [0002] Robot path planning has always been a research hotspot in the field of robot intelligent control. With the increasing application of UAVs in civilian and military applications, the problem of path planning in the three-dimensional space where UAVs are located has become more and more important. The power inspection and photovoltaic power generation equipment inspection in the civilian direction of the UAV, and the multi-mission point cruise of the UAV in the military direction all involve the multi-objective path planning problem in the three-dimensional space, that is, planning in the three-dimensional space A circuit that passes through all target points without obstacles and requires the total path distance to be minimized. [0003] Multi-t...

AI Technical Summary

Problems solved by technology

For the multi-objective path planning problem in three-dimensional space, the existing research is to split it into two independent problems, three-dimensional path planning and traveling salesman problem, first use path planning methods in three-dimensional space such as A* algorithm, RRT Algorithm and genetic algorithm plan the path between each target point, and find the path and path distance between any two target points, thus converting the problem into an ordinary traveling salesman who knows the path cost between each target point. problem, and then use dynamic programming, simulated annealing algorithm, and ant colony algorithm to solve the traveling salesman problem. Such a method requires a lot of time for path planning between each target point. As the number of target points increases, , the path planning between each target point has become the main time consumption of the problem and a huge computational burden

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