An Immuno-engineering Approach for Anomaly Detection in Swarm Robotics

Authors:
Huikeng Lau;Iain Bate;Jon Timmis
Affiliations:
Department of Computer Science, University of York, and School of Engineering and IT, Universiti Malaysia Sabah, Malaysia;Department of Computer Science, University of York,;Department of Computer Science, University of York, and Department of Electronics, University of York, Heslington, UK YO10 5DD
Venue:
ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems
Year:
2009

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Abstract

In this paper, we present the first stage of our research strategy to develop an immune-inspired solution for detecting anomalies in a foraging swarm robotic system with an immuno-engineering approach. Within immuno-engineering, the initial stage of our research involves the understanding of problem domain, namely anomaly detection, in a foraging swarm robotic system deployed in dynamic environments. We present a systematically derived set of activities for this stage derived with Goal Structuring Notation and results of experiments carried out to establish the time-varying behaviour and how anomalies manifest themselves. Our future work will then be used to select and tailor an appropriate AIS algorithm to provide an effective and efficient means of anomaly detection.