Self-adaptation for Mobile Robot Algorithms Using Organic Computing Principles

Jan Hartmann, Walter Stechele, Erik Maehle


Many mobile robot algorithms require tedious tuning of parameters and are, then, often suitable to only a limited number of situations. Yet, as mobile robots are to be employed in various fields from industrial settings to our private homes, changes in the environment will occur frequently. Organic computing principles such as self-organization, self-adaptation, or self-healing can provide solutions to react to new situations, e.g. provide fault tolerance. We therefore propose a biologically inspired self-adaptation scheme to enable complex algorithms to adapt to different environments. The proposed scheme is implemented using the Organic Robot Control Architecture (ORCA) and Learning Classifier Tables (LCT). Preliminary experiments are performed using a graph-based Visual Simultaneous Localization and Mapping (SLAM) algorithm and a publicly available benchmark set, showing improvements in terms of runtime and accuracy.
Original languageEnglish
Title of host publicationArchitecture of Computing Systems -- ARCS 2013
EditorsHana Kubátová, Christian Hochberger, Martin Danek, Bernhard Sick
Number of pages12
Volume 7767 LNCS
Place of PublicationBerlin, Heidelberg
PublisherSpringer Berlin Heidelberg
Publication date01.02.2013
ISBN (Print)978-3-642-36423-5
ISBN (Electronic)978-3-642-36424-2
Publication statusPublished - 01.02.2013
Event26th International Conference on Architecture of Computing Systems - Prague, Czech Republic
Duration: 19.02.201322.02.2013
Conference number: 95603


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