Multi-Query Path Planning for Exploration Tasks with an Unmanned Rotorcraft

This paper presents an online multi-query path planner for exploration tasks planned onboard an unmanned helicopter. While the desirable properties of roadmaps can be exploited in o ine path planning, the dynamic nature of exploration scenarios hinders to utilize conventional roadmap planners. Hence, the presented path planning approach utilizes a deterministically sampled roadmap which is dynamically indexed in real time. To address situations of partial terrain knowledge, the roadmap can be extended from its a priori dimensions towards locations of unknown terrain that are outside its original, a priori boundaries. The multi-query property of the planning system allows for combinatorial optimization such that a rapidly acting decisional autonomy is achievable during exploration ights. D*-Lite is used as dynamic heuristic path searcher in order to re-plan e ciently. Inspired by the original work on this path search algorithm, the roadmap graph is augmented with an exploration vertex which steers the exploration behavior of the vehicle. As a result, the presented roadmap guides an unmanned rotorcraft through a priori unknown urban terrain in real time.