A study on controlling multiple mobile robots using multiple software agents with evolutionary algorithms

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This project addresses optimizing distributed robotic control of systems using an example of an intelligent cart system designed to be used in common airports. This framework provides novel control methods using mobile software agents. In airport terminals, luggage carts used by traveler are taken from a depot but are left after use at arbitrary points. It would be desirable that carts be able to draw themselves together automatically after being used so that manual collection becomes less laborious. In order to avoid excessive energy consumption by the carts, we employ mobile software agents and RFID (Radio Frequency Identification) tags to identify the location of carts scattered in a field and then cause them to autonomously determine their moving behavior using a clustering method based on the ant colony optimization (ACO) algorithm.