基于双层启发RRT的轻小无人机路径规划研究

Reseach on Path Planning of Light and Small UAV Based on Two-layer Heuristic RRT

对复杂任务环境下的轻小无人机的路径规划问题进行了研究,提出了一种基于双层启发快速扩展随机树(RRT)的航迹规划方法。考虑轻小无人机的实际任务环境,建立其路径规划质点模型,给出了系统运动性能约束条件。在常规RRT方法中引入面向目标的启发式随机点采样启发和新节点扩展启发算法。在多个复杂威胁环境下的路径规划仿真结果表明,所提方法提高了到目标点的收敛速度,优化了飞行航迹的平滑度和可跟踪性。

To solve the trajectory planning problem of light and small Unmanned Aerial Vehicle （UAV） in complex task environment, a new trajectory planning method is proposed based on the two- layer heu- ristic rapid- exploring random tree（RRT） algorithm. Taking the real mission environment into considera- tion, the particle model of light and small UAV is established. Meanwhile,the constraints of system＇s motion performance condition is given. Then, the trajectory planning method of two- layer heuristic RRT algo- rithm is proposed, in which the object- oriented heuristic random sampling heuristic and the new node expansion heuristic are introduced to the traditional RRT. Simulation results in complex threat environment show that the proposed algorithm enhance the convergence speed to the target and optimize the smoothness and the traceability of the flight path.