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IMR-LLM: Industrial Multi-Robot Task Planning and Program Generation using Large Language Models
Xiangyu Su, Juzhan Xu, Oliver van Kaick +2
In modern industrial production, multiple robots often collaborate to complete complex manufacturing tasks. Large language models (LLMs), with their strong reasoning capabilities,…
RoboBPP: Benchmarking Robotic Online Bin Packing with Physics-based Simulation
Zhoufeng Wang, Hang Zhao, Juzhan Xu +8
Physical feasibility in 3D bin packing is a key requirement in modern industrial logistics and robotic automation. With the growing adoption of industrial automation, online bin pa…
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…
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…