Swarm Intelligent Route Planning of UAV with Elastic Track Correction

摘要

Main purpose of UAV path planning are shorten the distance, avoid flight threats and obstacles. Planning feasible path intervals is the basis of path planning. In long-distance, multi-obstacle path planning, it is more important to plan a reasonable distance and sufficient safety path. Therefore, aiming at the problem of complex track constraints in long-distance and multi-obstacle path planning, a new method of track initialization and adjustment named elastic track correction is proposed to make up for the limitations of current track initialization and solution space. Using wolf pack intelligence algorithm as validation algorithm, this paper compares the effectiveness of elastic track correction mechanism with that of general planning method, which proves that adding elastic correction mechanism to track planning algorithm can effectively improve the reliability of track planning, and can get a feasible solution of lower cost function.