1 citations · 2 across the 3 of their papers we have counts for
4 papers
Physical AI: A Survey of Models, Learning, Systems, and Open Challenges
Bin Gao, Anuj Gautam, Aritra Bagchi +17
Physical AI aims to enable intelligent systems to perceive, reason, act, and learn through interaction with the physical world. Unlike purely digital intelligence, physical agents…
INTENTION: Inferring Tendencies of Humanoid Robot Motion Through Interactive Intuition and Grounded VLM
Jin Wang, Weijie Wang, Boyuan Deng +3
Traditional control and planning for robotic manipulation heavily rely on precise physical models and predefined action sequences. While effective in structured environments, such…
Learning to Recover: Dynamic Reward Shaping with Wheel-Leg Coordination for Fallen Robots
Boyuan Deng, Luca Rossini, Jin Wang +3
Adaptive recovery from fall incidents are essential skills for the practical deployment of wheeled-legged robots, which uniquely combine the agility of legs with the speed of wheel…
HYPERmotion: Learning Hybrid Behavior Planning for Autonomous Loco-manipulation
Jin Wang, Rui Dai, Weijie Wang +3
Enabling robots to autonomously perform hybrid motions in diverse environments can be beneficial for long-horizon tasks such as material handling, household chores, and work assist…