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Run-Time Compositional Software Platform for Autonomous NXT Robots
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Author(s): Ning Gui (University of Antwerp, Belgium), Vincenzo De Florio (PATS Research Group, University of Antwerp, and iMinds, Belgium)and Chris Blondia (University of Antwerp, Belgium)
Copyright: 2013
Pages: 13
Source title:
Innovations and Approaches for Resilient and Adaptive Systems
Source Author(s)/Editor(s): Vincenzo De Florio (PATS Research Group, University of Antwerp and iMinds, Belgium)
DOI: 10.4018/978-1-4666-2056-8.ch008
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Abstract
Autonomous Robots normally perform tasks in unstructured environments, with little or no continuous human guidance. This calls for context-aware, self-adaptive software systems. This paper aims at providing a flexible adaptive middleware platform to seamlessly integrate multiple adaptation logics during the run-time. To support such an approach, a reconfigurable middleware system “ACCADA” was designed to provide compositional adaptation. During the run-time, context knowledge is used to select the most appropriate adaptation modules so as to compose an adaptive system best-matching the current exogenous and endogenous conditions. Together with a structure modeler, this allows robotic applications’ structure to be autonomously (re)-constructed and (re)-configured. This paper applies this model on a Lego NXT robot system. A remote NXT model is designed to wrap and expose native NXT devices into service components that can be managed during the run-time. A dynamic UI is implemented which can be changed and customized according to system conditions. Results show that the framework changes robot adaptation behavior during the run-time.
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