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A NOVEL MACHINE VISION-BASED MOBILE ROBOT NAVIGATION SYSTEM IN AN UNKNOWN ENVIRONMENT

机译:未知环境中基于新型机器视觉的移动机器人导航系统

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摘要

A novel and efficient auto-navigation system based on machine vision for an unknown environment is developed in this study. A 3D model using only the measurements of a single image is implemented for 3D object measuring and map-building. For path-planning, the A~* algorithm is combined with the Floyd's shortest path to determine the optimal sub-goals in the image sensing range. The performance of the present method is compared to those of the Bug algorithm, virtual force field (VFF) path planning, genetic algorithm (GA) path planning and fuzzy logic control (FLC) path planning and shows overall better results in a cluttered environment. Further, the 3D map-building of the environment map is successfully accomplished.
机译:在这项研究中,开发了一种新颖的,高效的基于机器视觉的自动导航系统。仅使用单个图像的测量值的3D模型实现了3D对象测量和地图构建。对于路径规划,将A〜*算法与弗洛伊德(Floyd)最短路径结合起来,以确定图像传感范围内的最佳子目标。将本方法的性能与Bug算法,虚拟力场(VFF)路径规划,遗传算法(GA)路径规划和模糊逻辑控制(FLC)路径规划的性能进行比较,并在混乱的环境中显示出总体更好的结果。此外,成功完成了环境地图的3D地图构建。

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