The BDD-Based Dynamic A* Algorithm for Real-Time Replanning

Authors:
Yanyan Xu;Weiya Yue;Kaile Su
Affiliations:
State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China and School of Information Science and Engineering, Graduate University of the Chinese A ...;University of Cincinnati, Cincinnati, USA;Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, Beijing, China
Venue:
FAW '09 Proceedings of the 3d International Workshop on Frontiers in Algorithmics
Year:
2009

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Abstract

Finding optimal path through a graph efficiently is central to many problems, including route planning for a mobile robot. BDD-based incremental heuristic search method uses heuristics to focus their search and reuses BDD-based information from previous searches to find solutions to series of similar search problems much faster than solving each search problem from scratch. In this paper, we apply BDD-based incremental heuristic search to robot navigation in unknown terrain, including goal-directed navigation in unknown terrain and mapping of unknown terrain. The resulting BDD-based dynamic A* (BDDD*) algorithm is capable of planning paths in unknown, partially known and changing environments in an efficient, optimal, and complete manner. We present properties about BDDD* and demonstrate experimentally the advantages of combining BDD-based incremental and heuristic search for the applications studied. We believe that our experimental results will make BDD-based D* like replanning algorithms more popular and enable robotics researchers to adapt them to additional applications.