Proactive Safety Techniques and Applications for Industrial Robots

doi:10.3901/JME.2025.15.174

Abstract

Abstract: In current industrial manufacturing scenarios, robots often suffer from limited perception and lack intelligent interaction strategies, leading to frequent safety accidents, ranging from minor injuries to fatalities. To address the multi-source perception and safety interaction needs in future smart factories, a proactive safety operation concept for industrial robots is proposed, combining on-body and off-body perception. The system is built using a multi-source sensory network, which integrates wide-area visual monitoring, close-range proximity sensing, and collision detection. These technologies process and analyze proximity and contact signals, allowing for the design of shared human-robot control strategies and proactive safety operation planning. Furthermore, after dividing the sensor detection ranges, a Kalman filter-based multi-source fusion method is employed to process the multi-level perception signals and design tiered safety interaction strategies. The proactive safety system developed in this study has been integrated and tested in various platforms of Dongfang electric group, including the shock-type turbine water-wheel robot arc additive manufacturing platform and the large-diameter disc turbine rotor welding platform. The results demonstrate that the proposed multi-source fusion proactive safety method effectively combines the advantages of different sensors in various perception zones, providing perceptual capabilities and safety responses for human-robot interaction in full-space and full-scenario environments. This significantly enhances the safety and operational capability of industrial robot systems.

Key words: human-robot interaction safety, proximity sensing, industrial robots, proactive safety, human-centered smart manufacturing

CLC Number:

TP242

Lü Honghao, ZHU Zhengjie, CHENG Yuhang, HE Ping, WANG Ruohan, CHEN Fuguo, YANG Huayong, YANG Geng, DONG Na. Proactive Safety Techniques and Applications for Industrial Robots[J]. Journal of Mechanical Engineering, 2025, 61(15): 174-184.

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