3 papers
cs.RO2026
ViTacPhys: Physical Property-Aware Grasping from Human Visual-Tactile Demonstrations
Yiwen Liu, Yujun Zhu, Kui Jia +3
Recent vision-based action models have demonstrated strong capabilities in complex manipulation, but they rarely leverage explicit object physical properties to adapt their policie…
cs.RO2025
Reinforcement Learning for Robotic Safe Control with Force Sensing
Nan Lin, Linrui Zhang, Yuxuan Chen +5
For the task with complicated manipulation in unstructured environments, traditional hand-coded methods are ineffective, while reinforcement learning can provide more general and u…
cs.RO2020
NEARL: Non-Explicit Action Reinforcement Learning for Robotic Control
Nan Lin, Yuxuan Li, Yujun Zhu +6
Traditionally, reinforcement learning methods predict the next action based on the current state. However, in many situations, directly applying actions to control systems or robot…