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cs.RO2024
Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning
Zhecheng Yuan, Tianming Wei, Shuiqi Cheng +3
Can we endow visuomotor robots with generalization capabilities to operate in diverse open-world scenarios? In this paper, we propose \textbf{Maniwhere}, a generalizable framework…
cs.RO2024★ 3 cited
RoboScript: Code Generation for Free-Form Manipulation Tasks across Real and Simulation
Junting Chen, Yao Mu, Qiaojun Yu +11
Rapid progress in high-level task planning and code generation for open-world robot manipulation has been witnessed in Embodied AI. However, previous studies put much effort into g…