Tian LE

[Han Xue @HanXue012]

RoboPocket excels in the wild. We deploy a fleet to 4 different users in 4 distinct scenes. With just 12 interactive corrections per scene, success rates jumped from ~0.50 to >0.80. This proves the scalability of distributed human-in-the-loop refinement without hardware limits. 🌍 [6/n]

[Wendi Chen @wendi_chen_]

What if you could debug and improve robot policies using just an iPhone? 📱🤯

Super excited to share RoboPocket! We realize robot-free post-training with AR Visual Foresight and Instant Online Fine-tuning. Dive into the thread below to see it in action! 🚀👇

[Han Xue @HanXue012]

Check out our full paper and videos below! Website: https://robo-pocket.github.ioArxiv: https://t.co/m6pX4azwXh done w/
@junjie_fang_, @wendi_chen_, @uimicro, @Tiam_Lme, Yi Wang, Yuting Zhang, @JunLv98, @ChuanWen15, and @lucewu.