Showing cs.ROShow all
3 papers · 1 filter
cs.RO2026
IOI: Decoupling Kinematics and Physics for Interactive World Models
Chengyu Bai, Peidong Jia, Tiecheng Guo +11
Developing generalist embodied agents requires interactive environments providing visually realistic feedback and accurate action-conditioned dynamics. Interactive world models add…
cs.RO2026
MuseVLA: An Adaptive Multimodal Sensing Vision-Language-Action Model for Robotic Manipulation
Xingyuming Liu, Ruichun Ma, Heyu Guo +7
Humans naturally leverage diverse sensing modalities to interact with the physical world, while most Vision-Language-Action (VLA) models for robotics rely solely on RGB observation…
cs.RO2026
SafeDojo: Safe Reinforcement Learning for VLA via Interactive World Model
Kai Tang, Peidong Jia, Zhong Chu +15
Safe control is a prerequisite for real-world embodied intelligence, for which safe reinforcement learning has emerged as a promising paradigm. However, existing safe reinforcement…