A double-layer coding model with a rotation-based particle swarm algorithm for unmanned combat aerial vehicle path planning. (November 2022) - Jia, Yingjuan; Qu, Liangdong; Li, Xiaoqin
Abstract: Unmanned combat aerial vehicle (UCAV) technology has to address many challenges in complex battlefield environments. To produce a safe and low-energy flying path, a UCAV requires many points to build a path that avoids threats, which increases the problem dimension, consumes more computational resources and makes the results unstable. To address this issue, this paper employs a new model known as double-layer coding (DLC) for path planning with unevenly distributed points to decrease the number of superfluous points on the path. Meanwhile, the RPSO algorithm, which introduces a novel strategy of rotating particles in high-dimensional space to search for targets, is proposed as an enhanced particle swarm optimization (PSO) algorithm. The proposed method effectively improves PSO ′ s exploration capacity. Furthermore, RPSO is employed to implement the double-layer coding model for path planning (DLCRPSO). The experimental results show that the proposed DLCRPSO method for path planning always produces feasible flight paths in complex environments. Graphical abstract: Highlights: A double-layer coding model for path planning is established. An improved PSO with a novel exploration strategy is proposed. The superiority of the double-layer coding model used improved PSO is verified.