Neuro-fuzzy algorithm for obstacle avoidance mission of a mobile robot using FPGA

Chan Zhi Wei, Muhammad Nasiruddin Mahyuddin
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引用次数: 7

Abstract

Navigation and obstacle avoidance are some of the important tasks or mission deployed and accomplished by an autonomous mobile robot. This paper presents the designed obstacle avoidance program for mobile robot that incorporates a neuro-fuzzy algorithm using Altera Field Programmable Gate Array (FPGA) development board. To generate collision-free path for mobile robot, a proper motion planning is needed. The neuro-fuzzy-based-obstacle avoidance program is simulated and implemented on the hardware system using Altera Quartus® II design software, System-on-programmable-chip (SOPC) Builder, Nios® II Integrated Design Environment (IDE) software, and FPGA development and education board (DE2). Simulation and weight training process are carried out with the aid of Nios® II IDE software. A mobile robot serves as the test platform of the program. An ultrasonic sensor and servo motors are used as the test platform's sensing element and actuator, respectively. The neuro-fuzzy algorithm is successfully implemented on the Altera FPGA development board and tested with our remote mobile robot for obstacle avoidance missions via an established radio frequency (RF) communication.
基于FPGA的移动机器人避障任务的神经模糊算法
导航和避障是自主移动机器人部署和完成的一些重要任务。本文利用Altera现场可编程门阵列(FPGA)开发板,设计了一种基于神经模糊算法的移动机器人避障程序。为了生成移动机器人的无碰撞路径,需要进行适当的运动规划。利用Altera Quartus®II设计软件、系统级可编程芯片(SOPC) Builder、Nios®II集成设计环境(IDE)软件以及FPGA开发和教育板(DE2),在硬件系统上模拟和实现了基于神经模糊的避障程序。在Nios®II IDE软件的帮助下进行了模拟和重量训练过程。一个移动机器人作为程序的测试平台。测试平台的传感元件采用超声波传感器,执行机构采用伺服电机。神经模糊算法在Altera FPGA开发板上成功实现,并通过既定的射频(RF)通信在我们的远程移动机器人上进行了避障任务测试。
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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