Abstract:

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.