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cs.RO2025
Tracing Energy Flow: Learning Tactile-based Grasping Force Control to Reduce Slippage in Dynamic Object Interaction
Cheng-Yu Kuo, Hirofumi Shin, Takamitsu Matsubara
Regulating grasping force to reduce slippage during dynamic object interaction remains a fundamental challenge in robotic manipulation, especially when objects are manipulated by m…
cs.RO2025
Prolonging Tool Life: Learning Skillful Use of General-purpose Tools through Lifespan-guided Reinforcement Learning
Po-Yen Wu, Cheng-Yu Kuo, Yuki Kadokawa +1
In inaccessible environments with uncertain task demands, robots often rely on general-purpose tools that lack predefined usage strategies. These tools are not tailored for particu…
cs.RO2020
Uncertainty-aware Contact-safe Model-based Reinforcement Learning
Cheng-Yu Kuo, Andreas Schaarschmidt, Yunduan Cui +2
This letter presents contact-safe Model-based Reinforcement Learning (MBRL) for robot applications that achieves contact-safe behaviors in the learning process. In typical MBRL, we…