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A distributed genetic algorithm for swarm robots obstacle avoidance

Nesma M. Rezk, Yousra Alkabani, Hassan Bedor, Sherif Hammad

发表年份
2014
引用次数
9

摘要

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.

关键词

Obstacle avoidanceRobotGenetic algorithmSpeedupComputer scienceObstacleSwarm roboticsSwarm behaviourTask (project management)Artificial intelligence

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