Mobile Robot Online Motion Planning Using Generalized Voronoi Graphs

In this paper, a new online robot motion planner is developed for systematically exploring unknown environments by intelligent mobile robots in real-time applications. The algorithm takes advantage of sensory data to find an obstacle-free start-to-goal path. It does so by online calculation of the Generalized Voronoi Graph (GVG) of the free space, and utilizing a combination of depth-first and breadth-first searches on the GVG. The planner is equipped with components such as step generation and correction, backtracking, and loop handling. It is fast, simple, complete, and extendable to higher spaces.