【摘要】 在模糊几何地图的基础上提出了顶点定位法来解决机器人的室内SLAM中的实时自定位问题．顶点定位法是从传感信息中抽取多边形顶点作为路标进行定位．顶点定位法与传统的边匹配定位法比较有计算量小,定位精度高等优点．此外本文提出了基于空间距离的传感数据两次分类方法构建模糊几何地图,提高了数字地图精确度．实验结果表明其性能优于传统的方法．更多还原

【Abstract】 This paper proposes a vertex self-localization method based on fuzzy geometric maps to solve the real-time localization of in-door SLAM (simultaneously localization and map building) problem. The vertex self-localization is to extract the vertexes of polygons as the landmarks from the raw sensor information. Compared with the traditional edge match method, vertex self-localization has higher accuracy and less computational complexity. A novel twice-classification method is also proposed to improve the precision of digital maps. Finally, experimental results are given to show that our method is more efficient than the traditional edge match method.更多还原