ROBOG:具有简单学习策略的机器人指南

Y. Harish, R. K. Kumar, G. M. D. I. Feroz, C. Jada, V. A. Kumar, Mounika Mesa
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引用次数: 4

摘要

本文介绍了ROBOG;一个自主机器人的实验成果,它可以学习已知地形的导航系统,并使用它来引导。它配备了人工神经网络来完成决策任务。ROBOG被训练来学习RGUKT学术街区地板的地理结构,并成功地引导一个人从任何地方到训练区域的任何特定教室。采用误差反向传播算法和粒子群算法对人工神经网络进行训练。结果表明,粒子群算法在训练人工神经网络方面优于传统的EBP算法。它也可以很容易地被训练成其他类型的结构。对今后的工作和扩展提出了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ROBOG: Robo guide with simple learning strategy
This paper presents ROBOG; an experimental effort in building an autonomous robot that can learn the navigation system of a known terrain and use it for guiding. It is equipped with Artificial Neural Network for the task of Decision making. ROBOG was trained to learn the geographical structure of a floor in an academic block of RGUKT and is tested successfully to guide a person from anywhere to any specific classroom in the trained region. The training of ANN is done with Error Back Propagation algorithm and Particle Swarm Optimization. Results are provided showing the superiority of PSO over conventional EBP in training the ANN. It can easily be trained for other type of structures as well. Some outlook of future work and extensions are suggested.
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