English(EN) Modeling Robotics Dataset Construction as an Artifact-Based Build Process

Bagzel 通过基于构件的构建过程简化机器人数据集创建

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-02 04:00

研究人员开发了 Bagzel，这是一个开源的 Bazel 扩展，旨在简化从机器人传感器数据创建机器学习数据集的过程。通过将数据集构建建模为基于构件的构建过程，Bagzel 旨在减少将 ROS bag 录制内容转换通常带来的工程开销和缓慢的迭代周期。评估表明，Bagzel 显著缩短了运行时间，尤其是在迭代和增量构建场景中，与传统的顺序脚本方法相比有了实质性改进。 AI

影响提高了机器人领域机器学习数据集生成的再现性和效率，有望加速研发。

排序理由该集群包含一篇详细介绍机器人数据集构建新方法和工具的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

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Newsworthiness bucket: Tool; 该集群包含一篇详细介绍机器人数据集构建新方法和工具的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Leon Pohl, Lukas Beer, George Sebastian, Mirko Maehlisch · 2026-06-02 04:00

将机器人数据集构建建模为基于构件的构建过程

arXiv:2606.00162v1 Announce Type: cross Abstract: Robotic systems generate large volumes of multimodal sensor data, but converting ROS bag recordings into machine learning datasets is often handled by ad hoc sequential scripts, creating engineering overhead and slow iteration cyc…

本文如何被排名

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将机器人数据集构建建模为基于构件的构建过程

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