The implementation of a novel, bio-inspired, robotic security system

  • Authors:

  • Robert Oates;Michael Milford;Gordon Wyeth;Graham Kendall;Jonathan M. Garibaldi

  • Affiliations:

  • The School of Computer Science, The University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham, UK;The School of Information Technology and Electrical Engineering and the Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia;The School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, Australia;The School of Computer Science, The University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham, UK;The School of Computer Science, The University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham, UK

  • Venue:
  • ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
  • Year:
  • 2009

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Abstract

The implementation of a robotic security solution generally requires one algorithm to route the robot around the environment and another algorithm to perform anomaly detection. Solutions to the routing problem require the robot to have a good estimate of its own pose. We present a novel security system that uses metrics generated by the localisation algorithm to perform adaptive anomaly detection. The localisation algorithm is a vision-based SLAM solution called RatSLAM, based on mechanisms within the hippocampus. The anomaly detection algorithm is based on the mechanisms used by the immune system to identify threats to the body. The system is explored using data gathered within an unmodified office environment. It is shown that the algorithm successfully reacts to the presence of people and objects in areas where they are not usually present and is tolerised against the presence of people in environments that are usually dynamic.