[1]刘重男,杨 洋,卢清心,等.低成本二维激光传感器室内移动建图方法研究[J].计算机技术与发展,2023,33(08):30-36.[doi:10. 3969 / j. issn. 1673-629X. 2023. 08. 005]
　LIU Zhong-nan,YANG Yang,LU Qing-xin,et al.Research on Indoor Mapping Based on Low-cost Two-dimensional Laser Sensor[J].,2023,33(08):30-36.[doi:10. 3969 / j. issn. 1673-629X. 2023. 08. 005]
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低成本二维激光传感器室内移动建图方法研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
33
期数:
2023年08期
页码:
30-36
栏目:
媒体计算
出版日期:
2023-08-10

文章信息/Info

Title:
Research on Indoor Mapping Based on Low-cost Two-dimensional Laser Sensor
文章编号:
1673-629X(2023)08-0030-07
作者:
刘重男; 杨 洋; 卢清心; 张 艺; 汪 沛*
北京林业大学 理学院,北京 100083
Author(s):
LIU Zhong-nan; YANG Yang; LU Qing-xin; ZHANG Yi; WANG Pei*
School of Science,Beijing Forestry University,Beijing 100083,China
关键词:
同时定位与建图; 室内自主建图; K 近邻算法; DBSCAN; 二维激光; 点云
Keywords:
SLAM; indoor independent mapping; KNN; DBSCAN; two-dimensional laser; point cloud
分类号:
TP242;TN958. 98
DOI:
10. 3969 / j. issn. 1673-629X. 2023. 08. 005
摘要:
随着机器人设备的广泛应用,室内自主建图作为设备行动的基础条件,也成为研究的热点。 基于低成本的二维激光传感器,该文提出一种室内移动自主建图的方法。 该方法通过在移动平台上安装低成本激光传感器获取单帧二维点云数据,采用 DBSCAN 方法对原始点云数据进行降噪预处理,结合点云近邻聚类并用线性最小二乘法拟合场景结构线段,经RMSE 阈值验证确认后,再结合室内结构特点调整线段,最终实现室内自主建图。 试验地点选择北京林业大学的四处室内场景,采用该方法采集和处理点云数据获得建图结果,同时手动测量进行比对。 分析结果表明,室内自主建图所获得的室内结构线段长度平均绝对误差为 3. 69 厘米,楼道宽度平均绝对误差为 2. 39 厘米。 该方法能够低成本实现室内移动建图,建图完整度较好,具有一定的可行性。
Abstract:
With the wide application of robot equipment, indoor mapping, as the basic condition of equipment action, has become aresearch hotspot. Based on a low-cost two-dimensional laser sensor and mobile platform,we propose an indoor autonomous mappingmethod. In the experiment,the low - cost laser sensor on a mobile platform is used to get the single frame of two - dimensional pointcloud. DBSCAN is used to pre-process the original point cloud data with noise reduction. Combined with point cloud nearest neighborclustering and linear least square method,the scene structure line segment is fitted. After RMSE threshold verification,the line segment isadjusted according to the indoor structure characteristics, and finally the indoor independent mapping is realized. The experiment iscarried out in four indoor scenes at Beijing Forestry University. The proposed method is used to collect and process the point cloud datato obtain the map construction results,and compared with the manual measurement at the same time. The analysis shows that the averageabsolute error of indoor structure line length and corridor width is 3. 69 cm and 2. 39 cm respectively. The proposed method canaccomplish the indoor mobile mapping with a lower costw,which is feasible and robust.
更新日期/Last Update: 2023-08-10