Metrological Evaluation of Human-Robot Collaborative Environments Based on Optical Motion Capture Systems

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.