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cs.RO2024
Pyramid-Monozone Synergistic Grasping Policy in Dense Clutter
Chenghao Li, Nak Young Chong
Grasping a diverse range of novel objects in dense clutter poses a great challenge to robotic automation mainly due to the occlusion problem. In this work, we propose the Pyramid-M…
cs.RO2024
An Efficient Deep Reinforcement Learning Model for Online 3D Bin Packing Combining Object Rearrangement and Stable Placement
Peiwen Zhou, Ziyan Gao, Chenghao Li +1
This paper presents an efficient deep reinforcement learning (DRL) framework for online 3D bin packing (3D-BPP). The 3D-BPP is an NP-hard problem significant in logistics, warehous…