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A fitness-sharing based genetic algorithm for collaborative Multi Robot Localization

Francesco Bori, Andrea Gasparri, Stefano Panzieri

Year
2009
Citations
5

Abstract

In this paper, a novel genetic algorithm based on a ¿collaborative¿ fitness-sharing technique to deal with the Multi-Robot Localization problem is proposed. Indeed, the use of the fitness-sharing is twofold and competitive. It preserves the diversity among individuals during the space exploration process, thus maintaining evolutionary niches over time, and reinforces the best hypotheses by means of collaboration among robots, thus augmenting the selection pressure. Simulations by exploiting the robotics framework Player/Stage have been performed along with a proper statistical analysis for performance assessment.

Keywords

RobotEvolutionary roboticsArtificial intelligenceComputer scienceSelection (genetic algorithm)Fitness functionGenetic algorithmProcess (computing)Evolutionary algorithmRobotics

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