EmbodiSteer: Steering Embodiment-Agnostic Visuomotor Policies with Joint-Space Guidance for Zero-Shot Cross-Embodiment Deployment
cs.RO
Submitted: 2026-06-11
Updated: 2026-10-13
Project page: https://frankwang67.github.io/EmbodiSteer-Page
Terminology
Sources
- 3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations
- OpenVLA: An Open-Source Vision-Language-Action Model
- X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model
- Rethinking Visual-Language-Action Model Scaling: Alignment, Mixture, and Regularization
- Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots
- Latent Action Diffusion for Cross-Embodiment Manipulation
- UniVLA: Learning to Act Anywhere with Task-centric Latent Actions
- LAP: Language-Action Pre-Training Enables Zero-shot Cross-Embodiment Transfer
- MetaMorph: Learning Universal Controllers with Transformers
- DexUMI: Using Human Hand as the Universal Manipulation Interface for Dexterous Manipulation
- UMI on Legs: Making Manipulation Policies Mobile with Manipulation-Centric Whole-body Controllers
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- Body Transformer: Leveraging Robot Embodiment for Policy Learning
- One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion
- Being-H0.7: A Latent World-Action Model from Egocentric Videos
- EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos
- EgoScale: Scaling Dexterous Manipulation with Diverse Egocentric Human Data
- Steering Your Diffusion Policy with Latent Space Reinforcement Learning
- From Demonstrations to Safe Deployment: Path-Consistent Safety Filtering for Diffusion Policies
- Classifier-Free Diffusion Guidance
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