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Vision and RTLS Safety Implementation in an Experimental Human-Robot Collaboration Scenario.

Juraj Slovák1, Markus Melicher1, Matej Šimovec1

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Summary

This study introduces an adaptive robotic workplace that enhances safety and collaboration by dynamically adjusting operation based on real-time stimuli. It integrates vision-based systems and real-time location systems to minimize downtime in human-robot collaboration.

Keywords:
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Area of Science:

  • Robotics
  • Industrial Automation
  • Computer Vision

Background:

  • Human-robot collaboration is increasing in industrial settings due to its flexibility.
  • Traditional safety measures are often insufficient for advanced collaborative environments.
  • Emerging technologies offer new solutions for safe and adaptive robotic workplaces.

Purpose of the Study:

  • To propose a novel safe robotic workplace system that adapts its operation and speed based on surrounding environmental stimuli.
  • To integrate advanced technologies for enhanced safety and seamless collaboration in industrial settings.
  • To reduce operational downtimes in collaborative robotic systems through innovative exception handling.

Main Methods:

  • Utilized a depth camera with passive stereo vision to establish dynamic safety zones and detect objects, calculating their distance via pixel shift.
  • Implemented the Histogram of Oriented Gradients (HOG) for precise human identification within the workspace.
  • Integrated a real-time location system (RTLS) with tags for unequivocal identification of autonomous trolleys supplying materials.

Main Results:

  • The system successfully identified objects and humans within safety zones, adjusting the robotic workplace's speed or halting operations accordingly.
  • Autonomous trolleys entering safety zones did not disrupt the workplace speed, demonstrating effective exception handling.
  • Simulations confirmed the system's compliance with safety measures in various operational scenarios.

Conclusions:

  • The integration of an RTLS with a vision-based safety system provides an innovative approach to exception handling in collaborative robotics.
  • This interconnected system enhances safety and collaboration while significantly reducing system downtimes.
  • The proposed adaptive robotic workplace represents a significant advancement in industrial automation safety and efficiency.