Diff-CAST replaces GAN discriminators with diffusion-based priors and adds symmetric command conditioning plus constrained RL to enable versatile, drift-free, and hardware-safe quadruped locomotion.
Ase: Large- scale reusable adversarial skill embeddings for physically simulated characters
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LineRides enables commandable bicycle robot stunts via line-guided RL that uses spatial guidelines, a tracking margin for feasibility, distance-based progress, and sparse key-orientations.
The Weightlessness Mechanism lets humanoid robots imitate non-self-stabilizing motions by dynamically relaxing specific joints to exploit passive environmental contacts, generalizing from single demonstrations to varied setups.
RPG trains a single policy with transition and timing randomization for stable multi-skill fighting on humanoids, integrated with locomotion for arbitrary-duration combat.
Switch enables humanoid robots to perform agile, seamless transitions between locomotion skills via a kinematic skill graph, DRL tracking policy, and real-time graph-search scheduler.
citing papers explorer
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Constraint-Aware Diffusion Priors for High-Fidelity and Versatile Quadruped Locomotion
Diff-CAST replaces GAN discriminators with diffusion-based priors and adds symmetric command conditioning plus constrained RL to enable versatile, drift-free, and hardware-safe quadruped locomotion.
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LineRides: Line-Guided Reinforcement Learning for Bicycle Robot Stunts
LineRides enables commandable bicycle robot stunts via line-guided RL that uses spatial guidelines, a tracking margin for feasibility, distance-based progress, and sparse key-orientations.
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Learn Weightlessness: Imitate Non-Self-Stabilizing Motions on Humanoid Robot
The Weightlessness Mechanism lets humanoid robots imitate non-self-stabilizing motions by dynamically relaxing specific joints to exploit passive environmental contacts, generalizing from single demonstrations to varied setups.
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RPG: Robust Policy Gating for Smooth Multi-Skill Transitions in Humanoid Fighting
RPG trains a single policy with transition and timing randomization for stable multi-skill fighting on humanoids, integrated with locomotion for arbitrary-duration combat.
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Switch: Learning Agile Skills Switching for Humanoid Robots
Switch enables humanoid robots to perform agile, seamless transitions between locomotion skills via a kinematic skill graph, DRL tracking policy, and real-time graph-search scheduler.