Online Creating an Improved UAV Path in Complex and Hostile Environments

We propose a cost based rapidly-exploring random tree method (CBRRT) to plan an improved path under complex obstacles and threats, limited deliberation time and constraints. The sampling space reduction of the dynamic domain rapidly-exploring random tree method (DDRRT) is improved and heuristics are applied, to guide the path tree to avoid threats and obstacles quickly, to rapidly find a low threat initial path. Meanwhile, the sampling space reduction is utilized to accelerate the path improving procedure of RRT* by limiting the path improving scope to appropriate areas. The reduction is constructed according to the real-time tree growth which provides the environmental information for DDRRT and RRT* as heuristic clues. The constraints and UAV motion are taken into account during the creation of the path. To make the path easier for UAV to follow, a cost based waypoints pruning method (CBP) is proposed, and the curvature-continuous Dubins curve is applied to smooth the path. The simulation results verify that CBRRT and CBP behave well in our environments.