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LLM-enhanced Scene Graph Learning for Household Rearrangement
Wenhao Li, Zhiyuan Yu, Qijin She +5
The household rearrangement task involves spotting misplaced objects in a scene and accommodate them with proper places. It depends both on common-sense knowledge on the objective…
Learning Cross-hand Policies for High-DOF Reaching and Grasping
Qijin She, Shishun Zhang, Yunfan Ye +2
Reaching-and-grasping is a fundamental skill for robotic manipulation, but existing methods usually train models on a specific gripper and cannot be reused on another gripper. In t…
Synchronized Dual-arm Rearrangement via Cooperative mTSP
Wenhao Li, Shishun Zhang, Sisi Dai +4
Synchronized dual-arm rearrangement is widely studied as a common scenario in industrial applications. It often faces scalability challenges due to the computational complexity of…
InterFusion: Text-Driven Generation of 3D Human-Object Interaction
Sisi Dai, Wenhao Li, Haowen Sun +5
In this study, we tackle the complex task of generating 3D human-object interactions (HOI) from textual descriptions in a zero-shot text-to-3D manner. We identify and address two k…
Learning Dual-arm Object Rearrangement for Cartesian Robots
Shishun Zhang, Qijin She, Wenhao Li +4
This work focuses on the dual-arm object rearrangement problem abstracted from a realistic industrial scenario of Cartesian robots. The goal of this problem is to transfer all the…