未知复杂环境中的无人机平滑飞行路径规划

Smooth path planning for unmanned aerial vehicles in unknown complex environments

针对无人机实时路径规划问题,提出了一种基于双层决策的平滑路径规划方法,以弥补现有方法在复杂飞行环境中对路径平滑性优化的不足,增强路径的易跟踪性.本文首先给出路径平滑性度量,然后建模上、下层决策目标、威胁规避与无人机性能约束并引入变长规划时间,进而设计基于双层决策的路径规划模型.规划过程中通过嵌入启发式优化策略来进一步改善路径的全局与局部平滑度,并提高路径搜索效率.大量复杂场景中的仿真及与现有经典方法的对比结果表明:该方法能够实时避开复杂危险区域,规划适合飞行的、较短的平滑路径.

A smooth real-time path planning approach is proposed based on the bilevel programming （BLP） for un- manned aerial vehicles （UAVs） in complex environments, to improve the flight path smoothness which has not been achieved by most existing methods. Firstly we define the measure for the path smoothness, and then we build the model for the bi-level decision objectives, the model of obstacle avoidances and the model of performances of the UAV, and intro- duce a variable planning time interval. On this basis, we proceed to develop the path planning model based on the bi-level decision. In the process of the planning, we introduce heuristic optimal strategies to further improve the smoothness for the local path and the global path, and to raise the efficiency in path searching. Results from simulations of the proposed approach in complex scenarios are compared with those obtained from classical methods; the conclusions indicate that the proposed approach can successfully plan a shorter and smoother flight path in real-time when passing around a wide dangerous region.