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

这个项目使用一个设计用于普通机场的智能手推车系统的例子来优化系统的分布式机器人控制。该框架使用移动软件代理提供了新颖的控制方法。在机场航站楼，旅客使用的行李车从仓库取走，但使用后留在任意地点。希望购物车在使用后能够自动组合在一起，从而减少手动收集的工作量。为了避免手推车过度消耗能量，我们使用移动软件代理和RFID(射频识别)标签来识别散布在田野中的手推车的位置，然后使用基于蚁群优化算法的聚类方法使它们自主确定其移动行为。

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.