4 accepted papers
Soft robots are inherently compliant and safe, making them suitable for humaninteractive applications such as surgery. However, their nonlinear and hysteretic behavior poses significant challenges for accurate modeling and control. We present a soft robotic system and propose a hysteresis-aware whol…
Soft robots are inherently compliant and safe, making them suitable for human-interactive applications such as surgery. However, their nonlinear and hysteretic behavior, arising from the properties of soft materials, presents substantial challenges for accurate modeling and control. In this study, w
Reinforcement learning (RL) for continuous control often requires large amounts of online interaction data. Value-based RL methods can mitigate this burden by offering relatively high sample efficiency. Some studies further enhance sample efficiency by incorporating offline demonstration data to “…
Large Vision-Language Action (VLA) models have shown significant potential for embodied AI. However, their predominant training via supervised fine-tuning (SFT) limits generalization due to susceptibility to compounding errors under distribution shifts. Reinforcement learning (RL) offers a path to…