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Application of Artificial Bee Colony Programming to Two Trails of the Artificial Ant Problem

机译:人工蜜蜂菌落编程在人工蚂蚁问题中的应用

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摘要

Automatic navigation of mobile robots has an increasing importance in many application fields such as robotics, mining industry, underwater exploration, aerospace research, virtual environments and games. In this study, we use artificial bee colony programming (ABCP), which is a novel evolutionary computation based automatic programming method, to solve the artificial ant problem that is considered as one of the basic test problems in robotic path planning. In order to see the performance of this method, a series of experiments are carried out on Santa Fe and Los Altos Hills trails. The results are compared with those of genetic programming.
机译:移动机器人的自动导航在许多应用领域具有越来越重要的应用领域,如机器人,矿业,水下勘探,航空航天研究,虚拟环境和游戏。在这项研究中,我们使用人造蜂殖民地编程(ABCP),该编程(ABCP)是一种基于新的进化计算的自动编程方法,以解决被认为是机器人路径规划中的基本测试问题之一的人工蚂蚁问题。为了看到这种方法的性能,一系列实验是在Santa Fe和Los Altos Hills Trails上进行的。将结果与遗传编程的结果进行比较。

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