Angle and Heuristic Guided Probabilistic Foam for Local Path Replanning

Online planning and replanning methods are commonly used in unknown or dynamic environments to ensure path safety. In this paper, we proposed a novel local path replanning algorithm. We adapted Probabilistic Foam (PF) idea for reactive planning tasks. Probabilistic Foam infrastructure is selected for several reasons. Firstly, these types of planners are lightweight, and secondly, they ensure collision-free path generation. But they don’t guarantee path optimality. In this work, the latest achievement on the PF idea was further improved and adapted to local planning tasks. We proved that our algorithm produces shorter paths and more lightweight than alternatives by conducting qualitative and quantitative tests. We also test our algorithm as a local planner on coverage path tracking and 2d obstacle avoidance tasks designed for a quadrotor in a realistic simulation environment.