Route planning method and equipment based on path search and intelligent optimization, and medium

Abstract

The invention belongs to the technical field of unmanned aerial vehicle air route planning, and discloses an air route planning method and device based on path search and intelligent optimization and a medium, basic air route initialization is performed by using an A * algorithm in combination with a random search strategy, air route optimization is performed by using an improved particle swarm algorithm iteration, and air route point simplification is performed by using an air route point simplification strategy. And outputting a path planning result. The method comprises the following steps: completing initial search of an air route through a basic air route initialization stage, and generating a basic feasible air route; in the air route optimization stage, intelligent optimization of air route points is completed, and the air route fitness is improved; in the waypoint simplification stage, waypoints are simplified, and the flight ability of the air route is improved. The optimization degree and the planning efficiency of the planning result are improved, and the task execution capability of the unmanned aerial vehicle in wartime is improved. According to the method, the manual dependence is improved, personnel are liberated from a complex calculation process so as to concentrate on decision making and other fields depending on experience judgment, and the combat effectiveness is improved.

Description

technical field [0001] The invention belongs to the technical field of UAV route planning, and in particular relates to a route planning method, equipment and medium based on route search and intelligent optimization. Background technique [0002] UAV route planning refers to finding the optimal or feasible route from the starting point to the target point that meets the mission requirements and UAV performance indicators under certain constraints. UAV route planning is the basis of UAV mission planning and the technical prerequisite for UAV to realize intelligent flight and autonomous control. Quickly and accurately planning the optimal or optimal flight path is one of the important means to improve the mission efficiency of UAVs. [0003] At present, a variety of algorithms have been proposed for route planning in the industry, mainly including traditional algorithms (such as dynamic programming algorithms, etc.) and modern intelligent algorithms (such as A* algorithm, ge...

AI Technical Summary

Problems solved by technology

[0003] At present, a variety of algorithms have been proposed for route planning in the industry, mainly including traditional algorithms (such as dynamic programming algorithms, etc.) and modern intelligent algorithms (such as A* algorithm, genetic algorithm, particle swarm algorithm, ant colony algorithm, etc.), but traditional algorithms are only applicable Planning under a single constraint condition is difficult to deal with complex planning under multiple constraint conditions; the traditional A* algorithm has the defects of slow search speed and large memory space consumption. If the search accuracy is reduced, the calculation accuracy will be insufficient and the planning result will be The level of optimization is not high; optimization algorithms such as genetic algorithm and particle swarm optimization algorithm have problems of insufficient convergence and long calculation time

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