T-GMP learns a terrain-conditioned latent motion manifold via CVAE from demonstrations and integrates it into an adversarial pipeline with a foothold penalty for versatile, natural humanoid locomotion.
Run: Residual policy for natural humanoid locomotion,
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cs.RO 2years
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UNVERDICTED 2representative citing papers
SPRINT generates sprint trajectories for humanoids via spectral priors from five human motion sequences, achieving 6 m/s peak velocity with zero-shot sim-to-real transfer on Unitree G1.
citing papers explorer
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T-GMP: Terrain-conditioned Generative Motion Priors for Versatile and Natural Humanoid Locomotion
T-GMP learns a terrain-conditioned latent motion manifold via CVAE from demonstrations and integrates it into an adversarial pipeline with a foothold penalty for versatile, natural humanoid locomotion.
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SPRINT: Efficient Spectral Priors for Humanoid Athletic Sprints
SPRINT generates sprint trajectories for humanoids via spectral priors from five human motion sequences, achieving 6 m/s peak velocity with zero-shot sim-to-real transfer on Unitree G1.