MODELING OF MOBILE ROBOT WITH OBSTACLE AVOIDANCE USING FUZZY CONTROLLER

Mahabbat Khudaverdiyeva
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引用次数: 2

Abstract

This paper presents the modeling of a robot's navigation using ultrasonic sensors under uncertainty. The robot tries to avoid obstacles by using the fuzzy logic controller to process the data coming from three ultrasonic sensors. To assess the performance of fuzzy logic optimized robot navigation controller with ultrasonic sensors, which measure the distance by calculating the time spent on the object and its return, the obstacles are placed in front of, left, and right of the robot.  Mamdani fuzzy reasoning system is used for the designed controller for its intuitive properties and fewer setting parameters which reduces the amount of time spent on the programming of the controller. 25 rules are considered to cover a robot’s possible interactions with obstacles. For an easy understanding of navigation architecture and rapid algorithm implementation, in this paper, a MATLAB simulation framework is developed. MATLAB/Simulink is one of the best simulation tools required to design the architecture and verify algorithms with real-time constraints. Resultant models of the fuzzy optimized controller demonstrate the superior performance of the fuzzy logic controller with high adaptability to the environment while maintaining a sufficient level of accuracy. The designed fuzzy controller can be used in microprocessor/microcontroller-based robots owing to easiness in implementation and coding.
基于模糊控制器的移动机器人避障建模
提出了在不确定条件下利用超声波传感器对机器人导航进行建模的方法。机器人通过模糊逻辑控制器处理来自三个超声波传感器的数据,试图避开障碍物。为了评估带有超声波传感器的模糊逻辑优化机器人导航控制器的性能,通过计算在物体上花费的时间和返回的时间来测量距离,障碍物被放置在机器人的前面,左边和右边。设计的控制器采用了Mamdani模糊推理系统,该系统具有直观的特性,且设置参数少,减少了控制器编程的时间。25条规则被认为涵盖了机器人与障碍物的可能互动。为了便于理解导航体系结构和快速实现算法,本文开发了一个MATLAB仿真框架。MATLAB/Simulink是设计具有实时约束的体系结构和验证算法所需的最佳仿真工具之一。所得到的模糊优化控制器模型证明了模糊控制器在保持足够精度的同时对环境具有较高的适应性。所设计的模糊控制器易于实现和编码,可用于基于微处理器/微控制器的机器人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.50
自引率
0.00%
发文量
47
审稿时长
5 weeks
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