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Long-horizon Robotic Search and Classification using Sampling-based Motion Planning
2015
Robotics: Science and Systems XI
This paper presents the Rapidly-exploring Adaptive Search and Classification (ReASC) algorithm, a sampling-based algorithm for planning the trajectories of mobile robots performing real-time target search and classification tasks in the field. The proposed algorithm incrementally builds up a tree of solutions and evaluates the utility of each solution for identifying targets in an environment. An optimistic approximation for the classification utility is used, which reduces the computational
doi:10.15607/rss.2015.xi.010
dblp:conf/rss/Hollinger15
fatcat:5vma765mznew3bk35cfuk6kfmy