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A fitness-sharing based genetic algorithm for collaborative multi-robot localization

机译:基于适应度共享的遗传算法进行多机器人协作定位

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摘要

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.
机译:本文提出了一种基于“协作”适应度共享技术的遗传算法来解决多机器人定位问题。确实,健身共享的使用是双重的且具有竞争性。它在太空探索过程中保留了个体之间的多样性,从而随着时间的推移保持了进化ni,并通过机器人之间的协作强化了最佳假设,从而增加了选择压力。通过利用机器人框架Player / Stage进行仿真,并进行适当的统计分析以评估性能。

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