Path Planning Method of UAV Area Coverage Searching Based on PEGA
Zhao Chenha · Keji daobao · 2014
This paper proposes a new method for the shortest path planning of UAV coverage searching in irregular regions. First, the mission area was dispersed with rasterisation by using the detection range of airborne sensor, and the path planning problem of area coverage searching was translated into a travelling salesman problem that can be solved. Then, the genetic algorithm was improved by using the multi-group parallel algorithm frame and elitist strategy, and the fitness function of the algorithm was redesigned. The parallel elitist genetic algorithm was put forward to solve the TSP problem. Experimental results show that the proposed method is applicable to the path planning problem of UAV area coverage searching. The proposed PEGA algorithm had a high convergence speed and the optimal solution had satisfactory quality. Improving the fitness function reduced the case of long distance between two points connected, apparently optimizing the path planning results.