Data-Driven Configuration of Protective Separation Zones in Collaborative Robot Cells from Operator Occupancy

Abstract:The protective separation zone of a collaborative robot cell is commonly dimensioned for a worst case that disregards where the operator is actually present during the task. This paper presents a camera-based, data-driven method that configures this zone from observed operator occupancy. Operator positions accumulated over several production shifts are aggregated into an occupancy heatmap, from which a protective field is derived that trades off the achievable robot velocity against the required safety distance, following the speed and separation monitoring principle of ISO/TS 15066. The resulting configuration is advisory, that is, reviewed within the risk assessment rather than applied autonomously to the robot controller. The method, which builds on a pose-based perception pipeline with activity recognition, was evaluated in two operational cells at two industrial partners, where the protective field could be reduced by approximately 17% and a productivity increase of 9% was measured. However, adoption proved to depend on more than the demonstrated gain alone.

7 pages, 4 figures. Accepted for publication at the 2026 IEEE Stuttgart Conference on Automotive Production (SCAP). \c{opyright} 2026 IEEE

Robotics (cs.RO)

arXiv:2611.07621 [cs.RO]

(or arXiv:2611.07621v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2611.07621 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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