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A Mixed-Perception Approach for Safe Human-Robot Collaboration in Industrial Automation.

  • Mohammadi Amin F Institute of Mechatronics System, Zurich University of Applied Science, 8400 Winterthur, Switzerland.
  • Rezayati M Institute of Mechatronics System, Zurich University of Applied Science, 8400 Winterthur, Switzerland.
  • van de Venn HW Institute of Mechatronics System, Zurich University of Applied Science, 8400 Winterthur, Switzerland.
  • Karimpour H Mechanical Engineering Department, University of Isfahan, Isfahan 81746-73441, Iran.
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  • 2020-11-11
Published in:
  • Sensors (Basel, Switzerland). - 2020
artificial intelligence
collision detection
human action recognition
industrial automation
safe physical human–robot collaboration
English Digital-enabled manufacturing systems require a high level of automation for fast and low-cost production but should also present flexibility and adaptiveness to varying and dynamic conditions in their environment, including the presence of human beings; however, this presence of workers in the shared workspace with robots decreases the productivity, as the robot is not aware about the human position and intention, which leads to concerns about human safety. This issue is addressed in this work by designing a reliable safety monitoring system for collaborative robots (cobots). The main idea here is to significantly enhance safety using a combination of recognition of human actions using visual perception and at the same time interpreting physical human-robot contact by tactile perception. Two datasets containing contact and vision data are collected by using different volunteers. The action recognition system classifies human actions using the skeleton representation of the latter when entering the shared workspace and the contact detection system distinguishes between intentional and incidental interactions if physical contact between human and cobot takes place. Two different deep learning networks are used for human action recognition and contact detection, which in combination, are expected to lead to the enhancement of human safety and an increase in the level of cobot perception about human intentions. The results show a promising path for future AI-driven solutions in safe and productive human-robot collaboration (HRC) in industrial automation.
Language
  • English
Open access status
gold
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Persistent URL
https://susi.usi.ch/global/documents/26747
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