A Hand-Drawn Language for Human-Robot Collaboration in Wood Stereotomy

This study introduces a novel, hand-drawn language designed to foster human-robot collaboration in wood stereotomy, central to carpentry and joinery professions. Based on skilled carpenters' line and symbol etchings on timber, this language signifies the location, geometry of woodworking joints...

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Bibliographic Details
Published in:IEEE access 2023, Vol.11, p.100975-100985
Main Authors: Aguilera-Carrasco, Cristhian A., Gonzalez-Bohme, Luis Felipe, Valdes, Francisco, Quitral-Zapata, Francisco Javier, Raducanu, Bogdan
Format: Article
Language:English
Subjects:
Carpentry
Collaboration
Computer vision
Cooperation
Cooperative systems
hand-drawn language
Human-robot interaction
Joint geometry
Layout
Natural languages
Robot learning
Robots
Service robots
Symbols
timber-joinery layout
Visualization
wood stereotomy
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Summary:This study introduces a novel, hand-drawn language designed to foster human-robot collaboration in wood stereotomy, central to carpentry and joinery professions. Based on skilled carpenters' line and symbol etchings on timber, this language signifies the location, geometry of woodworking joints, and timber placement within a framework. A proof-of-concept prototype has been developed, integrating object detectors, keypoint regression, and traditional computer vision techniques to interpret this language and enable an extensive repertoire of actions. Empirical data attests to the language's efficacy, with the successful identification of a specific set of symbols on various wood species' sawn surfaces, achieving a mean average precision (mAP) exceeding 90%. Concurrently, the system can accurately pinpoint critical positions that facilitate robotic comprehension of carpenter-indicated woodworking joint geometry. The positioning error, approximately 3 pixels, meets industry standards.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3314337