Article

Collision Avoidance with Deep Learning in a Digital Twin for Industrial Collaborative Robot Manipulation

2026-07-09

Abstract excerpt

Safe human-robot collaboration continues to present a critical challenge in manufacturing. Traditional safety approaches, such as cages and proximity sensors, are often insufficient for dynamic human interaction. This paper presents a digital twin-based collision avoidance framework for industrial collaborative robot manipulation. The system integrates RGB-D sensing, YOLO-based human pose estimation, Kalman-filter...

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Literature Corpus work: 7c283c3b-b77a-5b23-bab7-0fe662f87ffe
DOI: 10.20944/preprints202607.0628.v1

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