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Fuzzy Logic Controller for Obstacle Avoidance of Mobile Robot

机译:用于避免移动机器人的模糊逻辑控制器

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This work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using 'S-function' directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.
机译:这项工作描述了使用Fuzzy Logic用于四轮移动机器人的导航和避免控制器的设计和实现。本文的主要贡献可以总结在单一模糊逻辑控制器可用于导航以及四轮移动机器人动态模型的导航以及避免障碍物(静态,动态和两者)。键盘图用于开发移动机器人的动态模型,然后通过直接从符号Shakti键盘图软件库中使用“函数”将其转换为Simulink块。本工作中使用的四轮移动机器人配备了直流电动机,三个超声波传感器,用于测量距离障碍物和光学编码器的距离,以提供当前位置和速度。在模糊逻辑控制器中考虑了三个输入隶属函数(距离目标,角度和距离距离的距离)和两个输出隶属功能(左轮电压和右轮电压)。考虑了一百六十二套规则,用于移动机器人的运动控制。考虑不同的案例研究,并使用Matlab-Simulink软件平台进行模拟,以评估控制器的性能。仿真结果表明,导航和障碍物避免模糊控制器的性能在各种情况下的最小行进路径方面。

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