Retrieval from motion datasets combined with LLM task parsing and reward-guided noise initialization enables training-free diffusion optimization to satisfy severe spatiotemporal constraints in human motion generation.
Gmt: General motion tracking for humanoid whole-body control
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
years
2026 6verdicts
UNVERDICTED 6representative citing papers
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.
AWARE is a hierarchical RL framework that enables wheeled-legged robots to perform high-dynamic reflexive obstacle evasion with emergent gaits in simulation and on the real M20 platform.
A diffusion-based motion generator combined with an RL motion tracker enables terrain-aware whole-body locomotion on a humanoid robot by adapting reference motions online from perception.
HEX is a new framework with humanoid-aligned state representation, mixture-of-experts proprioceptive predictor, history tokens, and residual-gated fusion that achieves state-of-the-art success and generalization on real humanoid manipulation tasks.
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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Towards Highly-Constrained Human Motion Generation with Retrieval-Guided Diffusion Noise Optimization
Retrieval from motion datasets combined with LLM task parsing and reward-guided noise initialization enables training-free diffusion optimization to satisfy severe spatiotemporal constraints in human motion generation.
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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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Unleashing the Agility of Wheeled-Legged Robots for High-Dynamic Reflexive Obstacle Evasion
AWARE is a hierarchical RL framework that enables wheeled-legged robots to perform high-dynamic reflexive obstacle evasion with emergent gaits in simulation and on the real M20 platform.
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Learning Whole-Body Humanoid Locomotion via Motion Generation and Motion Tracking
A diffusion-based motion generator combined with an RL motion tracker enables terrain-aware whole-body locomotion on a humanoid robot by adapting reference motions online from perception.
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HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation
HEX is a new framework with humanoid-aligned state representation, mixture-of-experts proprioceptive predictor, history tokens, and residual-gated fusion that achieves state-of-the-art success and generalization on real humanoid manipulation tasks.
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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.