Abstract
Robot anomaly detection method described in this paper uses an approach inspired by an immune system for detecting failures within autonomous robot system. The concept is based on self-nonself discrimination and clonal selection principles found within the natural immune system. The approach applies principles of fuzzy logic for representing and processing the information within the artificial immune system. Throughout the paper we explain the working principle of RADE (Robot Anomaly Detection Engine) approach and we show its practical effectiveness through several experimental test cases.
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Jakimovski, B., Maehle, E. (2008). Artificial Immune System Based Robot Anomaly Detection Engine for Fault Tolerant Robots. In: Rong, C., Jaatun, M.G., Sandnes, F.E., Yang, L.T., Ma, J. (eds) Autonomic and Trusted Computing. ATC 2008. Lecture Notes in Computer Science, vol 5060. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69295-9_16
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DOI: https://doi.org/10.1007/978-3-540-69295-9_16
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