Environment-adaptive Bat Algorithm For UAV Path Planning
Zhanyu Chen, Jiawei Zhong, Xuejing Lan, Ge Ma, Wenbiao Xu · 2022
The main purpose of this paper is to solve the path planning problem of UAV in complex environment. In order to get rid of the local extremum and enhance its convergence ability, this paper proposes an environment-adaptive bat algorithm (EABA) with proper convergence ability in different environments. The convergence ability of the EABA can be adjusted by the particle swarm optimization (PSO) algorithm. At the same time, the obstacle avoidance is achieved in the path planning. In the simulation experiment, the proposed EABA was compared with the traditional BA and PSO. By evaluating the generated paths, the simulation results show the effectiveness and good performance of the proposed EABA.