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Visual Localization for Mobile Robots Based on Composite Map

机译:基于复合地图的移动机器人视觉定位

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摘要

In this paper, we propose a novel mobile robot visual localization method consisting of two processing stages: map construction and visual localization. In the map construction stage, both laser range finder and camera are used to construct a composite map. Depth data are collected from laser range finder while distinct features of salient feature points are gathered from camera provided images. In the visual localization stage, only camera is used and the robot system detects feature points from camera provided images, computes features of the detected feature points, matches them with the features recorded in previously constructed composite map, and decides location of the robot. Using this method, a robot can locate its own position effectively without expensive laser range finder so that greater acceptance can be expected due to affordability. With the proposed method, several experiments have been performed. The matching accuracy of proposed feature extraction achieves 97.79%, compared with 92.96% of SURF. Experiment results show that our method not only reduces hardware cost of robot localization, but also offers high accuracy.
机译:在本文中,我们提出了一种新颖的移动机器人视觉定位方法,该方法包括两个处理阶段:地图构建和视觉定位。在地图构建阶段,同时使用激光测距仪和照相机来构建合成地图。深度数据是从激光测距仪收集的,而显着特征点的独特特征是从摄像机提供的图像中收集的。在视觉定位阶段,仅使用摄像机,并且机器人系统会从摄像机提供的图像中检测特征点,计算检测到的特征点的特征,将它们与先前构建的合成地图中记录的特征进行匹配,并确定机器人的位置。使用这种方法,机器人可以有效地定位自己的位置,而无需昂贵的激光测距仪,因此由于价格合理,可以期望获得更大的接受度。利用所提出的方法,已经进行了一些实验。提出的特征提取的匹配精度达到97.79%,而SURF的匹配精度为92.96%。实验结果表明,该方法不仅降低了机器人定位的硬件成本,而且具有较高的精度。

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