基于改进直线特征提取算法的室内移动机器人地图构建

Indoor Mobile Robot Map Construction Based on Improved Linear Feature Extraction Algorithm

为使室内移动机器人更好地从充满噪声的2D激光测距仪数据中构建精准地图,提出一种基于相似三角形去噪法则的改进算法。利用分裂算法从预处理数据中提取线段集合,通过改进相似三角形去噪法则对每两分裂点间的数据点进行去噪,将去噪后的数据重新进行分裂,并对每两相邻分裂点间的扫描点进行最小二乘直线拟合。实验结果表明,该算法有效降低部分有效点被剔除的数量,精确度和假阳性指标优于相似三角形去噪法和传统分裂合并算法,同时避免线段合并过程,提高环境建模的鲁棒性和精准性。

In order to make the indoor mobile robot better build the accurate map from the data of2D laser range finder with noise, an improved algorithm based on similar triangules denoising rule is proposed. Using the splitting algorithm to extract the rough line set from the preprocessing data, the data points between the two split points are denoised by improving the similar triangules denoising rule, and the denoised data are re-split, and scanning points are fitted in the data between each two split points by least square method. Experimental results show that the proposed algorithm can reduce the number of effective points which are eliminated, and the accuracy and false positive indexes are better than similar triangles denoising method and traditional split and mergeing algorithm, at the same time, the line segment merging process is basically avoided, and the robustness and accuracy of environment modeling are enhanced.