Abstract
Mastering complexity is one of the greatest challenges for future dependable information processing systems. Traditional fault tolerance techniques relying on explicit fault models seem to be not sufficient to meet this challenge. During their evolution living organisms have, however, developed very effective and efficient mechanisms like the autonomic nervous system or the immune system to make them adaptive and self-organising. Thus, they are able to cope with anomalies, faults or new unforeseen situations in a safe way. Inspired by these organic principles the control architecture ORCA (Organic Robot Control Architecture) was developed. Its aim is to transfer self-x properties from organic to robotic systems. It is described in this article with a specific focus on the way ORCA deals with dynamically changing uncertainties and anomalies.
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Brockmann, W., Maehle, E., Grosspietsch, KE., Rosemann, N., Jakimovski, B. (2011). ORCA: An Organic Robot Control Architecture. In: Müller-Schloer, C., Schmeck, H., Ungerer, T. (eds) Organic Computing — A Paradigm Shift for Complex Systems. Autonomic Systems, vol 1. Springer, Basel. https://doi.org/10.1007/978-3-0348-0130-0_25
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DOI: https://doi.org/10.1007/978-3-0348-0130-0_25
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