Multi-Object Rearrangement with Monte Carlo Tree Search
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Multi-Object Rearrangement with Monte Carlo Tree Search

Jan 19, 2021
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Abstract: In this work, we address a planar non-prehensile sorting task. Here, a robot needs to push many densely packed objects belonging to different classes into a configuration where these classes are clearly separated from each other. To achieve this, we propose to employ Monte Carlo tree search equipped with a task-specific heuristic function. We evaluate the algorithm on various simulated and real-world sorting tasks. We observe that the algorithm is capable of reliably sorting large numbers of convex and non-convex objects, as well as convex objects in the presence of immovable obstacles. Authors: Haoran Song*, Joshua A. Haustein*, Weihao Yuan, Kaiyu Hang, Michael Yu Wang, Danica Kragic, Johannes A. Stork (HKUST, KTH, Yale)

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