Grasp, See and Place: Efficient Unknown Object Rearrangement with Policy Structure Prior

arXiv:2402.15402v1 Announce Type: cross
Abstract: We focus on the task of unknown object rearrangement, where a robot is supposed to re-configure the objects into a desired goal configuration specified by an RGB-D image. Recent works explore unknown object rearrangement systems by incorporating learning-based perception modules. However, they are sensitive to perception error, and pay less attention to task-level performance. In this paper, we aim to develop an effective system for unknown object rearrangement amidst perception noise. We theoretically reveal the …

abstract arxiv cs.lg cs.ro explore focus image modules objects perception policy prior rgb-d robot systems type