WearMoCap:用于使用智能手表进行无处不在的机器人控制的多式姿势跟踪
Fabian C Weigend1, Neelesh Kumar2, Oya Aran2
1Interactive Robotics Laboratory, School of Computing and Augmented Intelligence (SCAI), Arizona State University (ASU), Tempe, AZ, United States.
WearMoCap是一个开源库,用于使用智能手表传感器跟踪人类姿势,从而实现机器人控制. 它实现了高精度,可与移动捕捉系统相提并论,用于各种应用.
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
- 可穿戴技术可穿戴技术
背景情况:
- 人类姿势跟踪对于机器人和人机交互至关重要.
- 现有的运动捕捉系统往往是繁的,并不无处不在.
- 智能手表传感器提供了一个潜在的不引人注目的和可访问的运动跟踪.
研究的目的:
- 介绍WearMoCap,这是一个开源库,用于使用智能手表传感器数据跟踪人类姿势.
- 通过准确的姿势预测,实现无处不在的机器人控制.
- 为了评估不同的传感器配置,以捕捉运动.
主要方法:
- 开发了WearMoCap,有三个模式:仅限手表,上臂和口袋.
- 从使用消费级设备的8个人类受试者收集了大规模的数据集.
- 评估了交付和远程操作任务的性能,与黄金标准的运动捕捉系统进行了比较.
主要成果:
- WearMoCap的精度在2厘米之内达到金级标准的运动捕捉系统.
- 上臂模式提供了最准确的手腕位置估计 (6.79厘米RMSE).
- 在交付和远程操作任务中证明了真实机器人应用程序的性能.
结论:
- WearMoCap为基于智能手表的人体姿势跟踪提供了强大而准确的解决方案.
- 开源图书馆促进了未来对机器人可穿戴运动捕捉的研究.
- 该系统是为无处不在的应用程序设计的,其中运动跟踪是必不可少的.
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