English(EN) CoDA: Co-Evolution of Data Engines and Action Policies

CoDA框架通过协同进化数据引擎和行动策略来增强机器人训练

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-16 04:00

研究人员开发了CoDA框架，使数据引擎和行动策略能够为机器人训练进行协同进化。该系统使用共享内存将视觉语言批评家的诊断编译成生成程序，以重现困难和训练程序，帮助策略克服它们。CoDA显著提高了操纵任务中的分布外成功率，将成功率从5.3%提高到27.6%，并在位置扰动下的LIBERO-Pro上实现了84%的成功率。 AI

影响 CoDA的方法可以通过创建更有效的训练环境和更密集的监督信号来加速机器人学习。

排序理由该集群包含一篇详细介绍机器人训练新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Tianjiao Yu, Zhilin Ou, Yifan Shen, Xinzhuo Li, Yuanzhe Liu, Onkar Kishor Susladkar, Fan Wang, Ismini Lourentzou · 2026-10-16 04:00

CoDA: 数据引擎与行动策略的协同进化

arXiv:2610.22362v1 Announce Type: cross Abstract: Generative simulation can automate robot environment construction, but physically valid environments are not necessarily useful for training. The challenge is to identify environments that address a policy's failures and supervisi…

本文如何被排名

报道来源 [1]

CoDA: 数据引擎与行动策略的协同进化

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