基于P-L特征提取的SLAM地图构建算法

A point-to-line feature-based SLAM map building algorithm

针对室外环境中基于点特征的同时定位与地图构建(SLAM)算法中存在的计算复杂度与信息丰富度之间的矛盾,提出了提取室外环境点特征并转化为线特征的P-L(Point to Line)地图构建算法.通过连续提取的树木特征点,采取点-线匹配并保存线特征的方法设计地图关联的概率统计方案,将室内环境基于线特征的地图构建方法延伸到室外环境,形成SLAM地图构建中室外环境信息表达的新方法.选用鲁棒滤波算法,在MATLAB实验环境下进行仿真实验,结果表明,采用文中提出的方法可以降低信息表达的复杂度,验证了所提方法的可行性,为进一步室外场地跑车试验奠定了基础.

As there is a conflict between the requirements of computational complexity and information-richness within the point-feature based SLAM algorithm in outdoor environment, a point-to-line feature-based SLAM map building algorithm is presented in this paper. The tree information is sampled as point feature which is matched as line feature using math methods and associated to the map using the probability scheme. It is a new method to express the outdoor environment. A robust H∞ filter has been Used to simulate the feasibility of the algorithm with MATLAB, the result shows that the algorithm can reduce the complexity of the information expression, which establishes the foundation for vehicle experimentation.