外观
论文arXiv 2310.088642023-10-13
Open X-Embodiment发布RT-X模型与22机器人跨本体操作数据集
本文由 AI 根据公开内容整理，可能有误，请以原文为准：Open X-Embodiment: Robotic Learning Datasets and RT-X Models（arXiv 2310.08864）
核心内容
针对机器人学习长期存在的碎片化问题，21家研究机构联合推出Open X-Embodiment项目，旨在探索类似NLP领域的通用预训练范式。该项目整合了来自22种不同机器人平台的实操数据，构建了包含527项技能和160,266个任务的标准化大规模数据集，并开源了基于此训练的RT-X通用操作模型，为跨本体策略迁移研究提供了关键基础设施。
RT-X模型采用高容量架构，在统一格式的异构机器人数据上进行训练，实验证实其具备显著的正迁移特性，能利用其他平台的经验提升特定机器人的任务执行能力。该工作通过标准化数据接口解决了多源数据对齐难题，使研究者能在单一模型中探索从专用策略向通用X-robot策略的演进路径，相关资源已在项目官网开源。
关键看点
- 数据规模：集合22种机器人平台数据，覆盖527项操作技能与160,266个任务实例
- 模型架构：RT-X采用高容量Transformer架构，支持跨机器人、跨任务的正向迁移学习
- 协作生态：由21家机构联合构建，确立了机器人操作数据的标准化格式与共享协议
- 研究价值：验证了通用预训练模型在具身操作领域的可行性，打破单机单任务训练范式
工程与产业观察
Open X-Embodiment标志着具身智能从“小数据专用模型”迈向“大数据通用基座”的关键转折。其标准化的跨本体数据集与RT-X模型证明了操作技能的跨平台迁移潜力，为行业构建通用机器人大脑提供了可复现的数据底座与算法基准，将显著加速具身大模型的迭代效率。
英文摘要 (Abstract)
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train generalist X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. More details can be found on the project website https://robotics-transformer-x.github.io.
作者：Open X-Embodiment Collaboration, Abby O'Neill, Abdul Rehman, Abhinav Gupta, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain,…
来源
本页事实对应的公开页面，以原文为准。