研究人员开发了ATLAS，这是一种新的标注工具，旨在改进长时程机器人动作的标注过程。该工具提供多模态机器人数据（包括视频和本体感觉信号）的同步可视化，并支持ROS bag和RLDS等各种数据集格式。ATLAS旨在减少标注时间，提高用于训练机器人操作策略的时间动作分割的准确性。 AI
影响 通过简化数据标注，提高了训练机器人操作策略的效率和准确性。
排序理由 该集群包含两篇学术论文，介绍了用于机器人动作分割的新工具和方法。
AI 生成摘要 · Google Gemini · 来自 4 个来源。 我们如何撰写摘要 →
完整方法见我们的编辑标准。
arXiv:2604.26637v1 Announce Type: cross Abstract: Annotating long-horizon robotic demonstrations with precise temporal action boundaries is crucial for training and evaluating action segmentation and manipulation policy learning methods. Existing annotation tools, however, are of…
arXiv:2504.18662v3 Announce Type: replace-cross Abstract: Temporal action segmentation (TAS) has long been a key area of research in both robotics and computer vision. In robotics, algorithms have primarily focused on leveraging proprioceptive information to determine skill bound…
Annotating long-horizon robotic demonstrations with precise temporal action boundaries is crucial for training and evaluating action segmentation and manipulation policy learning methods. Existing annotation tools, however, are often limited: they are designed primarily for visio…
Annotating long-horizon robotic demonstrations with precise temporal action boundaries is crucial for training and evaluating action segmentation and manipulation policy learning methods. Existing annotation tools, however, are often limited: they are designed primarily for visio…