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dc.contributor.authorXu, Yanyanen_US
dc.contributor.authorYue, Weiyaen_US
dc.contributor.authorSu, Kaileen_US
dc.contributor.editorXiaotie Deng, John E. Hopcroft , and Jinyun Xueen_US
dc.description.abstractFinding 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.en_US
dc.publisher.placeUnited Statesen_US
dc.relation.ispartofconferencenameFAW 2009en_US
dc.relation.ispartofconferencetitleThird International Workshop, FAW 2009, Frontiers in Algorithmicsen_US
dc.relation.ispartoflocationHefei, Chinaen_US
dc.subject.fieldofresearchArtificial Intelligence and Image Processing not elsewhere classifieden_US
dc.titleThe BDD-Based Dynamic A* Algorithm for Real-Time Replanningen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.hasfulltextNo Full Text

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