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Article Abstract

This paper presents the development of a visual-perception system on a dual-arm mobile robot for human-robot interaction. This visual system integrates three subsystems. Hand gesture recognition is utilized to trigger human-robot interaction. Engagement and intention of the participants are detected and quantified through a cognitive system. Visual servoing uses YOLO to identify the object to be tracked and hybrid, model-based tracking to follow the object's geometry. The proposed visual-perception system is implemented in the developed dual-arm mobile robot, and experiments are conducted to validate the proposed method's effects on human-robot interaction applications.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739664PMC
http://dx.doi.org/10.3390/s22239545DOI Listing

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