Path planning with uncertainty: Voronoi Uncertainty Fields

In this paper, a two-level path planning algorithm that deals with map uncertainty is proposed. The higher level planner uses modified generalized Voronoi diagrams to guarantee finding a connected path from the start to the goal if a collision-free path exists. The lower level planner considers uncertainty of the observed obstacles in the environment and assigns repulsive forces based on their distance to the robot and their positional uncertainty. The attractive forces from the Voronoi nodes and the repulsive forces from the uncertainty-biased potential fields form a hybrid planner we call Voronoi Uncertainty Fields (VUF). The proposed planner has two strong properties: (1) bias against uncertain obstacles, and (2) completeness. We analytically prove the properties and run simulations to validate our method in a forest-like environment.