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A distributed genetic algorithm for swarm robots obstacle avoidance

机译:群体机器人避障的分布式遗传算法

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Obstacle avoidance is an extremely important task in swarm robotics as it saves robots from hitting objects and being damaged. A Genetic algorithm can be used to teach robots how to avoid obstacles in different environments. However the evaluation module of this genetic algorithm can be very time consuming module as each candidate solution should be evaluated N times. This paper explains the methodology used to distribute the evaluation module of genetic Algorithm over a cluster of computers to speed up the algorithm. The proposed methodology can be used for any application which suffers from time consuming evaluation module. Experimental results showed that the speedup can reach 70x.
机译:在群机器人中,避免障碍是一项极其重要的任务,因为它可以避免机器人撞到物体和损坏机器人。遗传算法可用于教机器人如何避免在不同环境中遇到障碍。然而,该遗传算法的评估模块可能是非常耗时的模块,因为每个候选解决方案都应评估N次。本文介绍了用于在一组计算机上分配遗传算法评估模块以加快算法速度的方法。所提出的方法可以用于遭受耗时的评估模块的任何应用。实验结果表明,加速比可以达到70倍。

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