Path Planning of UAV Based on Error Correction
Xia Liu, Yazhuo Li, Zhengyuan Xie · 2021
Abstract: Due to the limitation of system structure, UAV can not accurately locate itself. Once the positioning error accumulates to a certain extent, it may lead to mission failure. Therefore, the aircraft needs to go through several calibration points to correct vertical and horizontal error. In this paper, an improved ant colony optimization algorithm is used to realize path planning of the aircraft based on error correction. Firstly, mathematical model of path planning is established based on constraints of location error. Secondly, ant colony optimization is used to realize multi-objectives including maximizing success rate reaching the destination, minimizing the number of correction nodes and minimizing length of the path. To find feasible solutions for different problems, constraints are strengthened or relaxed and search strategies of the next node are set. Finally, the algorithm with adaptive parameters is verified by an example, the optimal path with 100% arrival rate, shorter length, and less correction nodes shows its effectiveness.