Human mobile robot interaction in the retail environment.
Human mobile robot interaction in the retail environment.
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DOI：
10.1038/s41597-022-01802-8
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发表时间：
2022-11-04
期刊：
影响因子：
9.8
通讯作者：
Hu, Boyi
中科院分区：
文献类型：
--
作者：
Chen, Yuhao;Luo, Yue;Yang, Chizhao;Yerebakan, Mustafa Ozkan;Hao, Shuai;Grimaldi, Nicolas;Li, Song;Hayes, Read;Hu, Boyi
随着技术的进步，人机交互（HRI）正在提高整体系统的效率和生产力。然而，让机器人与人类近距离接触，必然会对精确的人体运动跟踪和预测提出更高的要求。包含在共享空间中操作的人类和机器人的数据集正受到越来越多的关注，因为它们可以促进各种机器人和人类系统的研究。在日常活动中，除了视频图像之外，很少看到跟踪HRI的数据集。在本文中，我们介绍了一个新的数据集，专注于在面向未来的批发和零售贸易（WRT）环境中人类和机器人之间的社交导航（https：//uf-retail-cobot-cobot.github.io/）。八名参与者完成了消费者和零售工人通常承担的任务。收集了超过260分钟的数据，包括机器人和人类轨迹，人类全身运动捕捉，眼睛注视方向和其他上下文信息。包括对每个类别的数据流以及潜在用例的全面描述。此外，分析与多个数据源和未来的发展方向进行了讨论。
As technology advances, Human-Robot Interaction (HRI) is boosting overall system efficiency and productivity. However, allowing robots to be present closely with humans will inevitably put higher demands on precise human motion tracking and prediction. Datasets that contain both humans and robots operating in the shared space are receiving growing attention as they may facilitate a variety of robotics and human-systems research. Datasets that track HRI with rich information other than video images during daily activities are rarely seen. In this paper, we introduce a novel dataset that focuses on social navigation between humans and robots in a future-oriented Wholesale and Retail Trade (WRT) environment (https://uf-retail-cobot-dataset.github.io/). Eight participants performed the tasks that are commonly undertaken by consumers and retail workers. More than 260 minutes of data were collected, including robot and human trajectories, human full-body motion capture, eye gaze directions, and other contextual information. Comprehensive descriptions of each category of data stream, as well as potential use cases are included. Furthermore, analysis with multiple data sources and future directions are discussed.
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