基于网格PRM的无人机多约束航路规划

目前，无人机航路规划技术存在约束条件少,不能满足实际飞行需求,规划效率低等不足,文章主要针对上述问题提出改进措施。首先,将航路约束条件进行分类,提出了基本约束、平台安全约束和链路载荷约束,并对约束条件建模,完善无人机航路约束模型。为了提高无人机航路规划效率,提出了网格概率地图法(grid-probabilistic-roadmap, GPRM),利用约束模型构建代价函数,实现无人机航路的多约束快速航路规划。GPRM的实验仿真表明，GPRM规划效率相比较传统PRM有显著提升,同时规划结果更加符合实际任务需求,证明基于GPRM的无人机航路规划具有一定的工程应用价值。

Multi-constraints UAV path planning based on grid PRM

Nowadays the unmanned ariel vehicle (UAV)’s path planning technology has several defects, such as few constraints which lead to dissatisfactory of realistic flying demands, low efficiency in path planning, this paper mainly deals with these problems. First, classify the constraints into three types, basic constraints, platform safety constraints and link load constraints. Then model the constraints to refine UAV path constrain model. Next, to improve the planning efficiency the grid probabilistic roadmap (GPRM) method is proposed. Finally, by devising a cost function using constraint models, the high efficiency multi-constraints path planning for UAV is obtained. Simulations show that path planning using GPRM is faster than that using traditional PRM, and also notice that the path obtained by GPRM is more realistic for the actual flight, thus the engineer application value of this method is proved.