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About this paper
Lexing Zhang, Zeyu Zhang, Gang Zeng, Hangxin Liu
MoCo-Net predicts how far a movable part can move without collision and identifies likely collision points in a partial point cloud, then uses these predictions to guide rearrangement. In simulation, it reaches 82.4% collision-free success across 1,000 cluttered scenes, with 5.472 average rearrangement actions. On unseen-object tests, its range accuracy is 0.600; these results do not establish real-robot performance.
Summary by alphaXiv.
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