基于模糊神经网络的移动机器人自主运动

A. Cardenas, Javier G. Rázuri, D. Sundgren, R. Rahmani
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引用次数: 7

摘要

本文分析了模糊神经网络在移动机器人自主运动中的性能和实际实现。所设计的模糊神经控制器是传统模糊控制器的改进版,并被训练以优化给定的代价函数,使定位误差最小化。研究发现,采用模糊神经控制器的移动机器人对不同类型的期望轨迹具有良好的定位和跟踪性能。通过计算机仿真和实验室规模的类车机器人模型进行了实验验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autonomous Motion of Mobile Robot Using Fuzzy-Neural Networks
This paper analyzes the performance and practical implementation of fuzzy-neural networks for the autonomous motion of mobile robots. The designed fuzzy-neural controller is a refined version of a conventional fuzzy controller, and was trained to optimize a given cost function minimizing positioning error. It was found that the mobile robot with fuzzy-neural controller presents good positioning and tracking performance for different types of desired trajectories. It was verified by computer simulation as well as experimentally using a laboratory-scale car-like robot model.
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