ADP: Adversarial Dynamics Priors for Physically Grounded Humanoid Locomotion
In this paper, we propose Adversarial Dynamics Priors (ADP) for perturbation-resilient humanoid locomotion control. Existing motion prior-based methods induce natural motion styles by imitating kinematic motion features, but they do not directly regularize dynamics features, such as CoM motion, centroidal momentum, contact forces, and contact states. To address this limitation, we replace kinematic motion-style feature with selected dynamics features extracted from locomotion trajectories as the target of adversarial regularization. To this end, we use trajectory optimization to construct a reference dataset and train a discriminator to evaluate whether policy-induced temporal windows are...
| Authors | Seokju Lee, Jeongtae Lee, Jeonghyeok Lim et al. |
|---|---|
| Primary category | cs.RO |
| Published | 3 July 2026 |
| Last updated at source | 16 July 2026 |
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