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Research questionHow can humanoid robots anticipate future footholds when current visual observations are insufficient?On gaps, stepping stones, and narrow stairs, feasible contacts may be separated or difficult to infer from the immediately visible terrain. A poor foot-placement decision leaves little opportunity for recovery.
Computer Vision
Machine Learning
Reinforcement Learning
Robotics
Latest papersRecent research connected to this question, newest first.World-Model-Augmented Visual Locomotion for Humanoids on Foothold-Constrained TerrainThe evidence concerns a humanoid policy using proprioception and a single onboard depth stream, with experiments in simulation and on a physical Unitree G1 robot across gaps, stepping stones, and stairs. The reported approach uses a learned recurrent predictive representation with reinforcement learning, but the evidence does not establish performance beyond these terrain classes and settings.research paper · Sep 2, 2026
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