Brainwave-driven human-robot collaboration in construction

Yizhi Liu, Mahmoud Habibnezhad, Houtan Jebelli

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number103556
JournalAutomation in Construction
Volume124
DOIs
StatePublished - Apr 2021

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

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