在人机器人共存环境中,人类的连续组装和拆卸运动
Zhihao Liu1, Tianyu Wang2, Zhenrui Ji3,4
1Department of Production Engineering, KTH Royal Institute of Technology, Brinellvägen 68, Stockholm, 114 28, Sweden.
Scientific data
|November 11, 2025
概括
这项研究引入了一套新的数据集,用于分析人类在人类机器人共享空间中的移动. 它具有超过10,000个连续组装和拆卸运动的样本,有助于机器人学习和人类运动预测.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人与计算机的交互
- 计算机视觉 计算机视觉
背景情况:
- 人机系统日益普及,需要数据集来研究人类在共享环境中的行为.
- 现有的数据集往往忽视了诸如闭塞和人机交互中的各种人类行为等实际挑战.
研究的目的:
- 在人机器人共存环境中引入一种新的,大规模的数据集,用于人类连续组装和拆卸动作.
- 为机器人技术提供解决人类运动分析实际挑战的资源.
主要方法:
- 收集了来自多视图摄像机设置的10,000多个样本,包括同步的RGB视频和2D/3D人类骨架.
- 从33个不同的参与者收集了数据,捕捉了组装和拆卸任务.
- 数据集包括详细的注释 (时间,程序) 和Python代码用于可复制性.
主要成果:
- 使用最先进的深度学习模型进行技术验证,证明了数据集在实际应用中的潜力.
- 数据集有效地捕捉了诸如部分闭塞,重复运动和各种人类行为等挑战.
结论:
- 这一新型数据集将有助于推进人类运动预测和机器人顺序决策方面的研究.
- 它将支持自主机器人和人机器人协作政策的发展.
- 为研究人类在共享机器人环境中的行为提供了宝贵的资源.
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