任务(项目管理)
步伐
机器人
人机交互
可穿戴计算机
计算机科学
认知
人机交互
可穿戴技术
人工智能
机器人学
工程类
心理学
系统工程
嵌入式系统
大地测量学
地理
神经科学
作者
Yizhi Liu,Mahmoud Habibnezhad,Houtan Jebelli
标识
DOI:10.1016/j.autcon.2021.103556
摘要
Abstract Due to the unstructured, fast-changing environment of construction sites, robots require human assistance to perform various tasks, especially those involving high dexterity and nuanced human judgment. However, in shared physical spaces, human-robot collaboration (HRC) can raise new safety concerns as workers' mental health can be adversely affected by poor communication between the two peers. To create a harmonized, safe HRC, this study proposes a worker-centered collaborative framework that enables robots to capture workers' brainwaves from wearable electroencephalograph, evaluate their task-related cognitive load, and adjust the robotic performance accordingly. The framework was examined by asking 14 subjects to execute a collaborative construction task with a terrestrial robot under various levels of cognitive loads. The results showed the robot could regulate its working pace with 81.91% accuracy. This level of communication can instill trust in HRC and facilitate future endeavors in safety design of collaborative robotics.
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