Path planning for UAVs formation reconfiguration based on Dubins trajectory

• Published in: Journal of Central South University Vol. 25; no. 11; pp. 2664 - 2676
• Main Authors: Chen, Qing-yang, Lu, Ya-fei, Jia, Gao-wei, Li, Yue, Zhu, Bing-jie, Lin, Jun-can
• Format: Journal Article
• Language: English
• Published: Changsha Central South University 01.12.2018; Springer Nature B.V
• Subjects: Algorithms; Computer simulation; Engineering; Metallic Materials; Particle swarm optimization; Product design; Reconfiguration; Redundancy; Robustness (mathematics); Search and rescue missions; Trajectory optimization; Trajectory planning; Unmanned aerial vehicles; Dubins trajectory; 无人飞行器; 粒子群优化; unmanned aerial vehicles; 航迹规划; formation reconfiguration; path planning; particle swarm optimization; 队形重构; Dubins 轨迹
• ISSN: 2095-2899; 2227-5223
• DOI: 10.1007/s11771-018-3944-z

Multiple UAVs are usually deployed to provide robustness through redundancy and to accomplish surveillance, search, attack and rescue missions. Formation reconfiguration was inevitable during the flight when the mission was adjusted or the environment varied. Taking the typical formation reconfiguration from a triangular penetrating formation to a circular tracking formation for example, a path planning method based on Dubins trajectory and particle swarm optimization (PSO) algorithm is presented in this paper. The mathematic model of multiple UAVs formation reconfiguration was built firstly. According to the kinematic model of aerial vehicles, a process of dimensionality reduction was carried out to simplify the model based on Dubins trajectory. The PSO algorithm was adopted to resolve the optimization problem of formation reconfiguration path planning. Finally, the simulation and vehicles flight experiment are executed. Results show that the path planning method based on the Dubins trajectory and the PSO algorithm can generate feasible paths for vehicles on time, to guarantee the rapidity and effectiveness of formation reconfigurations. Furthermore, from the simulation results, the method is universal and could be extended easily to the path planning problem for different kinds of formation reconfigurations.