4 citations · 7 across the 11 of their papers we have counts for
11 papers · 1 filter
A Closed-Loop Multi-Agent Framework for Robust Multi-Robot Manipulation
Yi-Xiang He, Lan Wei, Haoming Cen +6
Multi-robot systems provide the parallelism and redundancy necessary for long-horizon tasks, while Large Language Models (LLMs) offer the reasoning capabilities to decompose these…
HATS: A Human-Agent Teleoperation System for Multi-Arm Data Collection
Zesen Lin, Jian-Jian Jiang, Haoming Cen +3
Many real-world manipulation scenarios, such as handling complex collaborative tasks and dealing with large workspaces, require coordination of more than two robotic arms. Conseque…
Task Editing for Generalizable 3D Visuomotor Policy Learning
Jian-Jian Jiang, YiHan Yang, Lan Wei +6
3D visuomotor policies offer a promising direction for complex robotic manipulation, as depth maps and point clouds provide rich geometric information for spatial reasoning. Howeve…
ReViP: Mitigating False Completion in Vision-Language-Action Models with Vision-Proprioception Rebalance
Zhuohao Li, Yinghao Li, Jian-Jian Jiang +6
Vision-Language-Action (VLA) models have advanced robotic manipulation by combining vision, language, and proprioception to predict actions. However, previous methods fuse proprioc…
Decomposed Object Manipulation via Dual-Actor Policy
Bin Fan, Jian-Jian Jiang, Zhuohao Li +5
Object manipulation, which focuses on learning to perform tasks on similar parts across different types of objects, can be divided into an approaching stage and a manipulation stag…
ODYSSEY: Open-World Quadrupeds Exploration and Manipulation for Long-Horizon Tasks
Kaijun Wang, Liqin Lu, Mingyu Liu +7
Language-guided long-horizon mobile manipulation has long been a grand challenge in embodied semantic reasoning, generalizable manipulation, and adaptive locomotion. Three fundamen…
Rethinking Bimanual Robotic Manipulation: Learning with Decoupled Interaction Framework
Jian-Jian Jiang, Xiao-Ming Wu, Yi-Xiang He +4
Bimanual robotic manipulation is an emerging and critical topic in the robotics community. Previous works primarily rely on integrated control models that take the perceptions and…
AffordDexGrasp: Open-set Language-guided Dexterous Grasp with Generalizable-Instructive Affordance
Yi-Lin Wei, Mu Lin, Yuhao Lin +4
Language-guided robot dexterous generation enables robots to grasp and manipulate objects based on human commands. However, previous data-driven methods are hard to understand inte…
Real-to-Sim Grasp: Rethinking the Gap between Simulation and Real World in Grasp Detection
Jia-Feng Cai, Zibo Chen, Xiao-Ming Wu +3
For 6-DoF grasp detection, simulated data is expandable to train more powerful model, but it faces the challenge of the large gap between simulation and real world. Previous works…
An Economic Framework for 6-DoF Grasp Detection
Xiao-Ming Wu, Jia-Feng Cai, Jian-Jian Jiang +3
Robotic grasping in clutters is a fundamental task in robotic manipulation. In this work, we propose an economic framework for 6-DoF grasp detection, aiming to economize the resour…
Grasp as You Say: Language-guided Dexterous Grasp Generation
Yi-Lin Wei, Jian-Jian Jiang, Chengyi Xing +5
This paper explores a novel task "Dexterous Grasp as You Say" (DexGYS), enabling robots to perform dexterous grasping based on human commands expressed in natural language. However…