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An extention of height value algorithm for micro-mouse robot applying for exploring unknown region

机译:微型鼠标机器人高度值算法在未知区域探索中的扩展

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The micro-mouse competition is gaining immense popularity universally. This paper proposes algorithm referred to the “extended height value algorithm” which is developed to an advanced level, so that the artificial robot could be made capable of exploring unknown regions such as micro-mouse competition maze. All of the 256 units in the standard 16∗16 units maze are given a series of numbers, which represent discretely assigned potential levels of turning into the crossway during exploring task. The numbers will be taken into consideration when the robot makes the crossway choice as well as autonomous route decisions. Then the choices will alter when the micro-mouse walks in order to optimize the exploring process. The paper also demonstrates effective measures to avoid duplication exploring as much as possible with artificial intelligence technique. In order to verify the developed algorithm, a simple, yet effective simulation program is coded to show that the improved algorithm has higher average efficiency compared with the less intelligent traditional algorithms.
机译:微型鼠标的竞争正在全球范围内获得极大的普及。本文提出了一种被称为“扩展高度值算法”的算法,该算法已发展到更高的水平,从而使该人造机器人能够探索未知区域,例如微型鼠标竞争迷宫。标准16 * 16单位迷宫中的所有256个单位均分配了一系列数字,这些数字代表在探索任务期间离散分配的进入十字路口的潜在水平。当机器人做出人行横道选择以及自主路线决定时,将考虑这些数字。然后,当微型鼠标行走时,选择将发生变化,以优化探索过程。本文还演示了有效的措施,以尽可能避免使用人工智能技术进行重复探索。为了验证所开发的算法,编写了一个简单而有效的仿真程序,以表明与智能程度较低的传统算法相比,改进后的算法具有更高的平均效率。

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