For perceptive humanoid locomotion, the relevance of terrain geometry depends on the robot's body state and how both evolve under its actions. Existing work has advanced terrain-aware sensory fusion and cross-modal prediction, improving how visual and proprioceptive information is combined and related. However, feature...
You Lyu, Cheng-Hao Sun, Zhen-Xuan Ding et al.· 0 citations
Humanoid soccer contact skills require more than producing high-impact foot-ball contacts: the robot must close the loop over perception, approach, alignment, impact, and recovery while its own motion induces substantial viewpoint changes, frequent loss of the ball from view, and uncertain contact outcomes. In this wor...
Jia-Kang Jin, Yi-Xiao Huo, Peng-Yuan Wang et al.· 0 citations
SkillX is presented, a unified reinforcement learning framework that learns and composes multiple atomic soccer skills through a single command-conditioned policy, enabling the robot to execute atomic skills and transition among them such as dribbling, trapping, and shooting.
Zhang-Chen Ye, En-Xuan Ruan, Yi-Fei Bao et al.· 2 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.