The Collaborative Kitting (CoKitting) approach in manufacturing combines human dexterity and robot repeatability to simplify assembly tasks, improving efficiency and safety. The proposed methodology aligns with the Industry 5.0 (I5.0) perspective, aiming at optimizing the collaborative task by proposing guidelines for both quantitative safety definition and reactive control algorithms. The first aspect is pursued by a review of the applicable norms and the development of advanced vision algorithms and AI-based strategies for the continuous human pose monitoring and behavioural models prediction with the objective of realising a real-time risk assessment. The second aspect anticipates interactions and minimises risks by introducing novel collision avoidance algorithms which re-plan in real time trajectories that avoid contact between the robot and any obstacles present in the work area, whether fixed or mobile, by considering the evaluated safety index.

Dynamic Safety Evaluation and Risk Mitigation Strategies for Collaborative Kitting

Bajrami A.;
2024-01-01

Abstract

The Collaborative Kitting (CoKitting) approach in manufacturing combines human dexterity and robot repeatability to simplify assembly tasks, improving efficiency and safety. The proposed methodology aligns with the Industry 5.0 (I5.0) perspective, aiming at optimizing the collaborative task by proposing guidelines for both quantitative safety definition and reactive control algorithms. The first aspect is pursued by a review of the applicable norms and the development of advanced vision algorithms and AI-based strategies for the continuous human pose monitoring and behavioural models prediction with the objective of realising a real-time risk assessment. The second aspect anticipates interactions and minimises risks by introducing novel collision avoidance algorithms which re-plan in real time trajectories that avoid contact between the robot and any obstacles present in the work area, whether fixed or mobile, by considering the evaluated safety index.
2024
9783031672941
9783031672958
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1266297
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