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cs.RO2026
TwinRL: Digital Twin-Driven Reinforcement Learning for Real-World Robotic Manipulation
Qinwen Xu, Jiaming Liu, Rui Zhou +11
Despite strong generalization capabilities, Vision-Language-Action (VLA) models remain constrained by the high cost of expert demonstrations and limited real-world interaction. Whi…
cs.RO2025
MOVE: A Simple Motion-Based Data Collection Paradigm for Spatial Generalization in Robotic Manipulation
Huanqian Wang, Chi Bene Chen, Yang Yue +7
Imitation learning method has shown immense promise for robotic manipulation, yet its practical deployment is fundamentally constrained by the data scarcity. Despite prior work on…
cs.RO2025
RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation
Shihan Wu, Xuecheng Liu, Shaoxuan Xie +81
Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due to the significant hardware hete…