Generates 48,000 synthetic VLK trajectories in 3D-reconstructed scenes to train a policy for egocentric perception-based humanoid navigation and object transport, shown on physical Unitree G1 robot.
Chip: Adaptive compliance for humanoid control through hindsight perturbation
6 Pith papers cite this work. Polarity classification is still indexing.
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cs.RO 6years
2026 6roles
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SceneBot conditions a humanoid tracking policy on motion references and contact labels, using reconstructed scene-interaction data to unify free-space locomotion with contact-rich manipulation and terrain tasks.
CEER proposes a compliant end-effector and root control interface that unifies loco-manipulation for humanoids via a distilled low-level policy and hierarchical planners.
ConstrainedMimic integrates operational space control and control barrier functions into RL tracking policies to enforce arbitrary runtime constraints on humanoid kinematics and dynamics while preserving contact modes and tracking goals.
HOIST finetunes a VLA policy from VR demonstrations then applies iterative batched RL to cut translational placement error by 19.9 cm and angular error by 3.56 degrees versus pure VLA on suspended-load manipulation.
HTD, a multimodal transformer policy trained with behavioral cloning and touch dreaming to predict future tactile latents, achieves a 90.9% relative success rate improvement over baselines on five real-world contact-rich humanoid loco-manipulation tasks.
citing papers explorer
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VLK: Learning Humanoid Loco-Manipulation from Synthetic Interactions in Reconstructed Scenes
Generates 48,000 synthetic VLK trajectories in 3D-reconstructed scenes to train a policy for egocentric perception-based humanoid navigation and object transport, shown on physical Unitree G1 robot.
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SceneBot: Contact-Prompted General Humanoid Whole Body Tracking with Scene-Interaction
SceneBot conditions a humanoid tracking policy on motion references and contact labels, using reconstructed scene-interaction data to unify free-space locomotion with contact-rich manipulation and terrain tasks.
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CEER: Compliant End-Effector and Root Control as a Unified Interface for Hierarchical Humanoid Loco-Manipulation
CEER proposes a compliant end-effector and root control interface that unifies loco-manipulation for humanoids via a distilled low-level policy and hierarchical planners.
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Constrained Whole-Body Tracking for Humanoid Robots
ConstrainedMimic integrates operational space control and control barrier functions into RL tracking policies to enforce arbitrary runtime constraints on humanoid kinematics and dynamics while preserving contact modes and tracking goals.
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HOIST: Humanoid Optimization with Imitation and Sample-efficient Tuning for Manipulating Suspended Loads
HOIST finetunes a VLA policy from VR demonstrations then applies iterative batched RL to cut translational placement error by 19.9 cm and angular error by 3.56 degrees versus pure VLA on suspended-load manipulation.
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Learning Versatile Humanoid Manipulation with Touch Dreaming
HTD, a multimodal transformer policy trained with behavioral cloning and touch dreaming to predict future tactile latents, achieves a 90.9% relative success rate improvement over baselines on five real-world contact-rich humanoid loco-manipulation tasks.