ArticleSensors (Basel, Switzerland)2021
Human-Machine Differentiation in Speed and Separation Monitoring for Improved Efficiency in Human-Robot Collaboration.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- LiDAR-Based Maintenance of a Safe Distance between a Human and a Robot Arm.Sensors (Basel, Switzerland) · 2023Article
- Human-Robot Collaboration in Industrial Automation: Sensors and Algorithms.Sensors (Basel, Switzerland) · 2022Article
- Task-Oriented Evaluation of the Feasible Kinematic Directional Capabilities for Robot Machining.Sensors (Basel, Switzerland) · 2022Article
- Prediction-Based Human-Robot Collaboration in Assembly Tasks Using a Learning from Demonstration Model.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
5 authors.
Funding
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Abstract
Human-robot collaborative applications have been receiving increasing attention in industrial applications. The efficiency of the applications is often quite low compared to traditional robotic applications without human interaction. Especially for applications that use speed and separation monitoring, there is potential to increase the efficiency with a cost-effective and easy to implement method. In this paper, we proposed to add human-machine differentiation to the speed and separation monitoring in human-robot collaborative applications. The formula for the protective separation distance was extended with a variable for the kind of object that approaches the robot. Different sensors for differentiation of human and non-human objects are presented. Thermal cameras are used to take measurements in a proof of concept. Through differentiation of human and non-human objects, it is possible to decrease the protective separation distance between the robot and the object and therefore increase the overall efficiency of the collaborative application.
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Registered trials
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