一种基于图像匹配的移动机器人定位方法

为增强移动机器人在非结构化动态环境下的定位能力，提出了一种基于图像相似度匹配的单目视觉粒子定位方法。在提取具有平移、旋转、缩放不变性的视觉特征基础上，引入相关核函数来提高特征对环境噪声和光照变化的适应性。利用以上局部特征，计算当前图像和参考图像的相似度作为粒子的权重，通过参考图像的可视区域更新粒子的后验概率分布。实验结果表明，该方法在不易提取几何特征的非结构化动态环境中能够实现可靠、高效的定位。

Approach for mobile robot localization based on images matching

To improve the localization capability of the mobile robot in a dynamic and unstructured environment,a mono-vision based particle filter localization approach is proposed. The localization is achieved by the computation of the similarity between query images and the images stored in an image database.After the extracting of the vision features which have the properties of invariance of translation,rotation and scale,a relational kernel function is applied to reduce the effect cased by environment noise and variations in illuminations.Based on the local features,the similarity is used as the weight of the particle and the post probability of the particle is updated by the visible areas of the reference images.The practical experiments illustrate that the approach is able to locate the robot accurately and effectively under the dynamic environment in which the geometry features are extracted difficultly.