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Fuzzy environment mapping for robot navigation based on grid computing

机译:基于网格计算的机器人导航模糊环境映射

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In order to navigate autonomously, a mobile robot needs to build an environment map where the robot is navigating. Currently, the sensors are mounted on the robot to detect if the obstacles exist and then the map immediate surrounding of the robot is built to help for navigation path planning. The map created by this method is a local map that may cause global navigation problem which a global coverage map is needed to solve such a problem. In this study, a sensor network is deployed for building global environment map. All the sensor locations are assumed known. The navigation space is divided into grids and a grid is to be detected if obstacles exist by one or a number of sensors. Fuzzy set concept is used to introduce a tool useful for sensor perception. Those sensors work as a team to explore all the space and then the global fuzzy map is constructed. The experiments show that the fuzzy map is more practical and helps the path planning problem to be solved more efficiently.
机译:为了自主导航,移动机器人需要在机器人导航时构建环境图。当前,将传感器安装在机器人上以检测障碍物是否存在,然后构建机器人周围的地图以帮助导航路径规划。通过这种方法创建的地图是可能导致全球导航问题的局部地图,需要全球覆盖图来解决该问题。在这项研究中,部署了传感器网络来构建全局环境图。假定所有传感器位置都是已知的。导航空间分为多个栅格,如果一个或多个传感器存在障碍物,则将检测一个栅格。模糊集概念用于引入对传感器感知有用的工具。这些传感器作为一个团队一起探索所有空间,然后构建全局模糊图。实验表明,模糊图更加实用,有助于更有效地解决路径规划问题。

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