Brainwave-driven human-robot collaboration in construction

• Published in: Automation in construction Vol. 124; p. 103556
• Main Authors: Liu, Yizhi, Habibnezhad, Mahmoud, Jebelli, Houtan
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.04.2021; Elsevier BV
• Subjects: Changing environments; Collaboration; Construction robots; Construction sites; Electroencephalogram (EEG); Human performance; Human-robot collaboration (HRC); Mental health; Robotics; Robots; Safety; Workers' cognitive load; Workplace safety and productivity; Construction robots; Workers' cognitive load; Human-robot collaboration (HRC); Electroencephalogram (EEG); Workplace safety and productivity
• ISSN: 0926-5805; 1872-7891
• DOI: 10.1016/j.autcon.2021.103556

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. •A field-oriented physiologically aware human-robot collaboration system is proposed.•The robot could continuously evaluate workers' mental states and react accordingly.•A collaboration between robot and worker based on their mental states is established.•The framework opens doors to new wearable sensor-based, human-robot collaboration.