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

Abstract

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 offline 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 flights. D*-Lite is used as dynamic heuristic path searcher in order to re-plan efficiently. 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.