Effective Human-Robot Collaboration Through Wearable Sensors
Effective Human-Robot Collaboration Through Wearable Sensors
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DOI：
10.1109/etfa46521.2020.9212100
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发表时间：
2020-09
期刊：
影响因子：
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通讯作者：
Ali Al-Yacoub;A. Buerkle;Myles Flanagan;P. Ferreira;Ella‐Mae Hubbard;N. Lohse
中科院分区：
文献类型：
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作者：
Ali Al-Yacoub;A. Buerkle;Myles Flanagan;P. Ferreira;Ella‐Mae Hubbard;N. Lohse
随着协作机器人在制造业中的发展，人与机器人之间的物理交互在协作执行任务中起着至关重要的作用。大多数进行的研究集中在机器人的运动规划和控制过程中执行的任务。然而，对于有效的任务分配和分配，人的生理和心理状态是必不可少的。在这项研究中，一套可穿戴传感器和数据采集框架的硬件设置和支持软件，开发。这可以用来开发更有效的人机协作策略。开发的框架旨在识别人类的精神状态和身体活动。随后，机器人可以有效地和自然地与人类一起执行给定的任务。此外，通过开发的硬件收集的数据可以在线分类人类的意图和活动;因此，机器人可以主动适应，以确保人类的安全，同时交付所需的任务。
With the developments of collaborative robots in manufacturing, physical interactions between humans and robots represent a vital role in performing tasks collaboratively. Most conducted studies focused on robot motion planning and control during the execution of a task. However, for effective task distribution and allocation, human physical and psychological status are essential. In this research, a hardware setup and support software for a set of wearable sensors and a data acquisition framework, are developed. This can be used to develop more efficient Human-Robot collaboration strategies. The developed framework is intended to recognise the human mental state and physical activities. Subsequently, a robot could effectively and naturally perform the given task with the human. Besides, the collected data through the developed hardware enables online classification of human intentions and activities; therefore, robots can actively adapt to ensure the safety of the human while delivering the required task.