arXiv
DexPort: A Hand-Held Skill Interface for Dexterous Hand Data Collection
Collecting high-quality demonstrations remains a central bottleneck for learning dexterous manipulat...
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arXiv
ViT-H: Generative Video-To-Humanoid Control with Motion Tracking Feedback
Learning humanoid control from monocular human videos offers a scalable way to acquire diverse whole...
arXiv
If at First You Don’t Succeed, Backtrack: Lightweight Recovery for Frozen VLAs
Vision-Language-Action (VLA) models perform well on robotic manipulation, yet remain brittle once th...
arXiv
SAGE: A hybrid vision-language and geometry framework for work-zone pathway prediction under temporary traffic control
Temporary traffic control redirects vehicles through work zones, requiring automated vehicles to con...
arXiv
Sensorimotor Alignment: A Platonic Proxy for Embodied Policy Success
Robotic foundation models are typically evaluated through costly closed-loop rollouts, which motivat...
arXiv
PhysiCalWorld: In-Context Physics Calibration for World Models
Existing world models typically perceive a scene through current visual frame or a narrow history wi...
arXiv
Multimodal Embodied Agents: A Unified Capability-centric Perspective from Computer-Use to Robot-Use
Multimodal agents (MMAs) sustain interaction through reasoning, memory, tools, and feedback, most vi...
arXiv
Asymmetric On-Policy Distillation Learns In-Context Exploration
Sequential decision-making under partial observability is difficult because agents must explore to i...
arXiv
AtomicRL: Atomic Reinforcement Learning for Long-Horizon Robotic Manipulation
Vision-language-action (VLA) models have shown promise in robotic manipulation, but imitation learni...
arXiv
Learning Adaptable Dexterous Skills via Hybrid Dexterous Mimicking
Dexterous multi-finger hands hold promise to unlock diverse skills like functional grasps, in-hand r...
arXiv
UniWALM: Unified World Action Language Model for Embodied Robot Control
Motivated by the human ability to integrate experience across language, perception, and action, we i...
arXiv
Industrial ReMEmbR: Scaling Spatiotemporal Memory to Robot Fleets
Warehouse robot fleets continuously observe operational conditions, but preserving these observation...
arXiv
Planning under Noise with Neural Operators
Planning under uncertain control execution noise requires reliable feedback policies across diverse ...
arXiv
Joints, Camera, Action! Co-Generating 3D Motion and Video for Arbitrary Rigs
Video generation models can now depict remarkably realistic motion.
arXiv
Ropedia W0: Scaling Loco-Manipulation World Models across Embodiments with Human Experience
World models enable embodied agents to anticipate action consequences, yet jointly modeling locomoti...