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ROBUST NAVIGATION TECHNIQUES FOR THE GVG-BASED SLAM IN UNSTRUCTURED ENVIRONMENT

机译:非结构化环境中基于GVG的SLAM的鲁棒导航技术

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The Generalized Voronoi Graph (GVG) has been effectively used for the SLAM and navigation of mobile robots. Since the mobile robot should perform the GVG-based SLAM and navigation in unstructured environments using inaccurate noisy sensors, it requires accurate data association and robust navigation techniques. In this paper, we suggest three techniques for a robust construction of the GVG. The first one is a robust node matching technique and the second one is an adaptable sensor area matching method for the robust exploration. Finally we propose a technique which is capable of distinguishing between closely located nodes. The simulation results show that the proposed algorithm can work successfully under 20% errors of odometry and range sensor in unstructured environment.
机译:广义Voronoi图(GVG)已有效地用于移动机器人的血液和导航。由于移动机器人应该使用不准确的噪声传感器执行基于GVG的SLAM和导航,因此需要准确的数据关联和强大的导航技术。在本文中,我们建议三种用于GVG的强大建设的技术。第一个是稳健的节点匹配技术,第二个是适用于鲁棒勘探的适应传感器区域匹配方法。最后,我们提出了一种能够区分密切所在节点的技术。仿真结果表明,该算法可以在非结构化环境中成功地在20%的内径测距和范围传感器误差下工作。

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