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Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
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Metrological Evaluation of Human-Robot Collaborative Environments Based on Optical Motion Capture Systems.

Leticia González1, Juan C Álvarez1, Antonio M López1

  • 1Multisensor Systems and Robotics Group (SiMuR), Department of Electrical, Electronic, Computer and Systems Engineering, University of Oviedo, C/Pedro Puig Adam, 33203 Gijón, Spain.

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This study introduces a new method to evaluate optical motion capture (OMC) systems for safe human-robot collaboration. The findings suggest optimal capture areas for OMC systems, ensuring reliable human motion tracking in shared environments.

Keywords:
calibrationgroupwarehuman–robot interactionindustrial robotsoptical tracking

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Area of Science:

  • Robotics
  • Human-Robot Interaction
  • Metrology

Background:

  • Optical motion capture (OMC) systems are increasingly used for human motion tracking in human-robot collaborative environments.
  • Assessing the accuracy and precision of OMC is crucial for ensuring safety in human-robot interactions.
  • Manufacturer specifications for OMC accuracy can be unreliable due to various measurement influencing factors.

Purpose of the Study:

  • To present a novel methodology for the metrological evaluation of OMC systems in human-robot collaborative environments.
  • To assess the performance of OMC systems based on mean error, error spread, and repeatability.
  • To identify optimal capture areas for OMC systems within a collaborative environment.

Main Methods:

  • A new methodology for metrological evaluation inspired by the ASTM E3064 test guide.
  • Utilizing an existing industrial robot within a production cell for system evaluation.
  • Conducting a detailed statistical study of error distribution across the capture area, including Mann-Whitney U-tests for median comparisons.

Main Results:

  • The proposed methodology effectively evaluates OMC systems for human-robot collaboration.
  • Statistical analysis revealed error distributions and allowed for median comparisons.
  • Optimal capture areas for the OMC system were identified based on the evaluation.

Conclusions:

  • The developed methodology provides a reliable way to assess OMC system performance in collaborative environments.
  • The metrological characteristics obtained are comparable to existing methods that do not require an industrial robot.
  • The study contributes to ensuring the safety and reliability of human-robot interactions through accurate motion tracking.