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Brainwave-driven human-robot collaboration in construction
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.
Highlights 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.
Brainwave-driven human-robot collaboration in construction
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.
Highlights 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.
Brainwave-driven human-robot collaboration in construction
Liu, Yizhi (Autor:in) / Habibnezhad, Mahmoud (Autor:in) / Jebelli, Houtan (Autor:in)
01.01.2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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