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Mobile robot visual navigation based on fuzzy logic and optical flow approaches

机译:基于模糊逻辑和光流方法的移动机器人视觉导航

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This paper presents the design of mobile robot visual navigation system in indoor environment based on fuzzy logic controllers (FLC) and optical flow (OF) approach. The proposed control system contains two Tak-agi-Sugeno fuzzy logic controllers for obstacle avoidance and goal seeking based on video acquisition and image processing algorithm. The first steering controller uses OF values calculated by Horn-Schunck algorithm to detect and estimate the positions of the obstacles. To extract information about the environment, the image is divided into two parts. The second FLC is used to guide the robot to the direction of the final destination. The efficiency of the proposed approach is verified in simulation using Visual Reality Toolbox. Simulation results demonstrate that the visual based control system allows autonomous navigation without any collision with obstacles.
机译:本文提出了基于模糊逻辑控制器(FLC)和光流(OF)方法的室内环境下移动机器人视觉导航系统的设计。所提出的控制系统包含两个基于视频采集和图像处理算法的Tak-agi-Sugeno模糊逻辑控制器,用于避障和目标寻找。第一转向控制器使用由Horn-Schunck算法计算出的OF值来检测和估计障碍物的位置。为了提取有关环境的信息,图像分为两个部分。第二个FLC用于将机器人引导到最终目的地的方向。使用Visual Reality Toolbox在仿真中验证了所提出方法的效率。仿真结果表明,基于视觉的控制系统可实现自主导航,而不会与障碍物发生任何碰撞。

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