标题: RoboPocket: Improve Robot Policies Instantly with Your Phone
作者: Junjie Fang, Wendi Chen, Han Xue, Fangyuan Zhou, Tian Le, Yi Wang, Yuting Zhang, Jun Lv, Chuan Wen, Cewu Lu
摘要: Scaling imitation learning is fundamentally constrained by the efficiency of data collection. While handheld interfaces have emerged as a scalable solution for in-the-wild data acquisition, they predominantly operate in an open-loop manner: operators blindly collect demonstrations without knowing the underlying policy's weaknesses, leading to inefficient coverage of critical state distributions. Conversely, interactive methods like DAgger effectively address covariate shift but rely on physical ...
arXiv ID: 2603.05504 分类: cs.RO, cs.AI, cs.LG 原文链接: https://arxiv.org/abs/2603.05504
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