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A review of external sensors for human detection in a human robot collaborative environment

Zainab Saleem (), Fredrik Gustafsson, Eoghan Furey, Marion McAfee and Saif Huq
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Zainab Saleem: Atlantic Technological University
Fredrik Gustafsson: Linköping University
Eoghan Furey: Atlantic Technological University
Marion McAfee: Atlantic Technological University
Saif Huq: 110 Kinsley Engineering Centre, York College of Pennsylvania

Journal of Intelligent Manufacturing, 2025, vol. 36, issue 4, No 3, 2255-2279

Abstract: Abstract Manufacturing industries are eager to replace traditional robot manipulators with collaborative robots due to their cost-effectiveness, safety, smaller footprint and intuitive user interfaces. With industrial advancement, cobots are required to be more independent and intelligent to do more complex tasks in collaboration with humans. Therefore, to effectively detect the presence of humans/obstacles in the surroundings, cobots must use different sensing modalities, both internal and external. This paper presents a detailed review of sensor technologies used for detecting a human operator in the robotic manipulator environment. An overview of different sensors installed locations, the manipulator details and the main algorithms used to detect the human in the cobot workspace are presented. We summarize existing literature in three categories related to the environment for evaluating sensor performance: entirely simulated, partially simulated and hardware implementation focusing on the ‘hardware implementation’ category where the data and experimental environment are physical rather than virtual. We present how the sensor systems have been used in various use cases and scenarios to aid human–robot collaboration and discuss challenges for future work.

Keywords: Sensors; Manipulators; Obstacle detection; Collaborative robots; Collision avoidance (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10845-024-02341-2

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