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Dynamic path planning and decentralized FLC path following implementation for WMR based on visual servoing

机译:基于视觉伺服的WMR动态路径规划和去中心化FLC路径跟踪

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This paper presents an implementation and practical results for dynamic path planning and robot navigation for a non-holonomic indoor wheeled mobile robot (WMR) based on visual servoing. The proposed algorithm is based on the visual information extracted from a single ceiled IP-camera in the overall its stages. The algorithm is divided into three stages; the first stage analyzes the working environment to plan a safe and optimal robot' path based on Multi-Stencils Fast Marching (MSFM) as a path-planning technique. Generally, the fast marching planning methods when used directly does not generate a safe path. Consequently, the robot can touch walls, corners, and obstacles. The proposed algorithm merges the image processing and MSFM to generate a safe and optimal shortest path. The second stage tracks the robot motion and estimates its position and orientation based on visual feature information. The third stage is the control loop algorithm, which is based on a proportional derivative Fuzzy Logic Controller (PD-like FLC) in a decentralized form, to keep up the robot on the desired path. Experimental results show the validity of the developed design to estimate the optimal path to avoiding moving obstacles and its ability to guide the robot to follow the desired path under variable conditions in real-time.
机译:本文提出了一种基于视觉伺服的非完整的室内轮式移动机器人(WMR)的动态路径规划和机器人导航的实现方法和实际结果。所提出的算法基于在整个阶段从单个天花板IP摄像机提取的视觉信息。该算法分为三个阶段。第一阶段基于多模板快速行进(MSFM)作为路径规划技术,分析工作环境以规划安全且最佳的机器人路径。通常,直接使用快速行进计划方法不会生成安全路径。因此,机器人可以触摸墙壁,角落和障碍物。所提出的算法将图像处理和MSFM合并,以生成安全且最佳的最短路径。第二阶段跟踪机器人运动并根据视觉特征信息估计其位置和方向。第三阶段是控制环算法,该算法基于分散形式的比例导数模糊逻辑控制器(PD-like FLC),以使机器人保持所需的路径。实验结果表明,开发的设计可有效估计避免移动障碍物的最佳路径,并具有指导机器人实时在可变条件下遵循所需路径的能力。

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