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Multisensor-based human detection and tracking for mobile service robots.

Nicola Bellotto1, Huosheng Hu

  • 1Human Centred Robotics Group, Department of Computing and Electronic Systems, University of Essex, CO4 3SQ Colchester, UK. n.bellotto@ieee.org

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|December 11, 2008
PubMed
Summary

This study presents a novel multisensor data fusion method for robust human tracking in service robots. The system effectively detects and localizes people using laser-based leg patterns and camera-based face detection, even in cluttered indoor environments.

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Area of Science:

  • Robotics
  • Computer Vision
  • Sensor Fusion

Background:

  • Effective human-robot interaction is crucial for service robots.
  • Accurate detection and tracking of people are essential for robots to provide services.
  • Existing methods face challenges in cluttered or dynamic environments.

Purpose of the Study:

  • To propose a robust human tracking solution for mobile service robots.
  • To develop a novel algorithm for laser-based leg detection.
  • To fuse multisensor data for improved person localization.

Main Methods:

  • Utilized a laser range finder (LRF) for leg pattern recognition.
  • Implemented a camera for face detection.
  • Employed a sequential unscented Kalman filter for data fusion.

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  • Developed algorithms for localizing static and walking persons.

    • Main Results:

    • Demonstrated effective leg pattern recognition in cluttered environments.
    • Achieved robust human tracking even when the robot is in motion.
    • Successfully fused laser and camera data for accurate localization.
    • Validated the approach on two different mobile robot platforms.

    Conclusions:

    • The proposed multisensor fusion approach enables robust human tracking for service robots.
    • The laser-based leg detection algorithm is effective in complex indoor settings.
    • The system is feasible for practical implementation on service robots.