EgoSteer: Full-Stack System for Steerable Dexterous Manipulation from Egocentric Videos

Jul 14, 2026

EgoSteer is a full-stack system that advances dexterous robot manipulation by scaling pre-training from 9,600 hours of egocentric human videos, curated via the EgoSmith pipeline. The system integrates a unified robot stack for teleoperation and a world-model-enhanced vision-language-action (VLA) model, enabling robust execution of free-form instructions across 40+ tasks. EgoSteer demonstrates few-shot adaptation to complex, long-horizon tasks with over 75% success, and supports language-guided manipulation with failure recovery and generalization.

Why it matters: This work represents a significant advance in scalable, steerable dexterous manipulation by bridging large-scale human video data and real-robot policy learning, enabling more general and robust robot capabilities.

Full story at: arXiv Robotics ↗