Motion Intention Recognition of Construction Workers for Human-Robot Collaboration in Construction
Publication: Construction Research Congress 2024
ABSTRACT
Construction robots have gained attention due to their potential for automating various construction tasks. Although recent research efforts have been made to develop robotic systems that assist manual work and reduce human intervention with different levels of automation, robots still need human assistance and collaboration for various tasks because of the unique characteristics of construction projects. To facilitate seamless human-robot collaboration in a dynamic and unstructured construction site, it is necessary that robots are able to understand not only the collaborator’s behavior in time but also its behavioral intention proactively to perform appropriate collaborative work. To achieve this goal, this study proposes a worker’s motion intention recognition method that captures the muscle activity of the workers using surface electromyography (sEMG) and detects motion intention from the muscle activity at the early stage of taking motions using a deep-learning approach. Using the sEMG signals, a deep-learning algorithm is used to predict the motion intention of the workers performing tasks for human-robot collaboration. With the proposed method, it is expected that robots can predict the motion that the worker in collaboration is going to take at the next moment, and ultimately this can improve the contextual awareness of robots for human-robot collaboration.
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Information & Authors
Information
Published In
Construction Research Congress 2024
Pages: 717 - 726
History
Published online: Mar 18, 2024
ASCE Technical Topics:
- Automation and robotics
- Business management
- Construction engineering
- Construction management
- Construction sites
- Continuum mechanics
- Dynamics (solid mechanics)
- Employment
- Engineering fundamentals
- Engineering mechanics
- Human and behavioral factors
- Labor
- Motion (dynamics)
- Personnel management
- Practice and Profession
- Project management
- Solid mechanics
- Systems engineering
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