Path planning for UAVs formation reconfiguration based on Dubins trajectory

Abstract

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.

摘要

由于无人飞行器编队的任务改变, 或者环境变化时, 编队队形重构的过程一般是难以避免的。 针对多无人飞行器进行目标观测的典型任务, 针对队形重构过程的实时航迹规划问题进行研究。为了 解决不同状态下三角队形与圆形队形变换过程的实时航迹规划问题, 提出一种融合Dubins 轨迹与粒 子群优化算法(PSO)的航迹规划方法。首先, 对多无人飞行器队形重构的航迹规划问题进行详细分 析, 建立高维的数学模型。接下来, 基于无人飞行器的基本运动学模型, 采用Dubins 轨迹对上述数 学模型进行降维。最后, 基于简化的数学模型, 采用PSO 优化算法进行实时求解。从仿真与飞行试 验结果可以看到, 基于Dubins 轨迹与PSO 算法的航迹规划方法, 能在队形变换过程中实时有效地生 成可行航迹。另外, 从仿真结果可以看到, 上述方法可以容易地拓展到不同队形的重构过程, 因此具 有较好的通用性。