A double-layer coding model with a rotation-based particle swarm algorithm for unmanned combat aerial vehicle path planning. (November 2022)

• Record Type: Journal Article
• Authors: Jia, Yingjuan; Qu, Liangdong; Li, Xiaoqin
• Is Part Of: Engineering applications of artificial intelligence. Volume 116(2022)
• Publication Date: 2022-11
• Subjects: Unmanned combat aerial vehicle -- Path planning -- Double-layer coding -- Particle swarm optimization -- Rotation-based exploration; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.105410
• Languages: English
• ISSNs: 0952-1976

Abstract

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.