EMMA: Scaling Mobile Manipulation via Egocentric Human Data

Understand

Scaling mobile manipulation imitation learning is bottlenecked by expensive mobile robot teleoperation.

• We present Egocentric Mobile MAnipulation (EMMA), an end-to-end framework training mobile manipulation policies from human mobile manipulation data with static robot data, sidestepping mobile teleoperation.
• To accomplish this, we co-train human full-body motion data with static robot data.
• In our experiments across three real-world tasks, EMMA demonstrates comparable performance to baselines trained on teleoperated mobile robot data (Mobile ALOHA), achieving higher or equivalent task performance in full task success.