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

机译:使用FPGA的移动机器人障碍物的神经模糊算法

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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 Quartusreg II design software, System-on-programmable-chip (SOPC) Builder, Niosreg 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 Niosreg 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.
机译:导航和避免是由自主移动机器人部署和完成的重要任务或任务。本文介绍了用于移动机器人的设计障碍物,它包括使用Altera现场可编程门阵列(FPGA)开发板的神经模糊算法。为了为移动机器人生成无碰撞路径,需要一个适当的运动规划。使用Altera Quartusreg II设计软件,可编程芯片(SOPC)Builder,NiosReg II集成设计环境(IDE)软件以及FPGA开发,模拟和实现了神经模糊的障碍物避税程序。和教育委员会(DE2)。借助NiosReg II IDE软件进行了仿真和体重训练过程。移动机器人用作程序的测试平台。超声波传感器和伺服电机分别用作测试平台的传感元件和执行器。在Altera FPGA开发板上成功实现了神经模糊算法,并通过已建立的射频(RF)通信,用我们的远程移动机器人进行障碍物避免任务。

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