most citedHierarchical Policy for Non-prehensile Multi-object Rearrangement with Deep Reinforcement Learning and Monte Carlo Tree Search

6 citations · 6 across the 1 of their papers we have counts for

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1 paper

cs.RO2021★ 6 cited

Hierarchical Policy for Non-prehensile Multi-object Rearrangement with Deep Reinforcement Learning and Monte Carlo Tree Search

Fan Bai, Fei Meng, Jianbang Liu +2

Non-prehensile multi-object rearrangement is a robotic task of planning feasible paths and transferring multiple objects to their predefined target poses without grasping. It needs…