TY - JOUR
T1 - Brainwave-driven human-robot collaboration in construction
AU - Liu, Yizhi
AU - Habibnezhad, Mahmoud
AU - Jebelli, Houtan
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/4
Y1 - 2021/4
N2 - 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.
AB - 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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U2 - 10.1016/j.autcon.2021.103556
DO - 10.1016/j.autcon.2021.103556
M3 - Article
AN - SCOPUS:85099837762
SN - 0926-5805
VL - 124
JO - Automation in Construction
JF - Automation in Construction
M1 - 103556
ER -