基于多源数据融合的室内平面地图构建方法
Indoor-Floor-Plan Construction Method Based on Multi-Source Data Fusion
冯冠元 1张健 1苗语 1蒋振刚 1师为礼 1金鑫2
作者信息
- 1. 长春理工大学计算机科学技术学院,吉林 长春 130012
- 2. 长春理工大学计算机科学技术学院,吉林 长春 130012;中国科学院航空光学成像与测量重点实验室,吉林 长春 130033
- 折叠
摘要
单一数据源信息不充分、传感器本身及传感器之间的标定存在误差导致室内地图创建不精准,针对这一问题,本文提出基于多源数据融合的室内平面图构建算法,该算法利用RGB-D传感器获取室内场景中的三维结构特征,并将其融入激光雷达点云中,从而构建具有三维结构特征的室内平面地图.在该算法中,先将RGB-D传感器中深度相机采集到的图像转换为伪激光雷达点云;然后,使用基于多项式函数拟合的过滤器对伪激光雷达点云进行分层和校准,并对激光雷达点云和伪激光雷达点云进行融合;最后,利用融合后的点云数据创建室内二维平面地图.实验结果表明,本文提出的点云分层过滤和校准方法可以有效融合激光雷达点云和伪激光雷达点云,融合点云构建的室内二维平面地图精度明显提高.
Abstract
To address the inaccuracies of indoor map construction due to insufficient information derived from single data sources and errors in multi-sensor calibration,an indoor floor plan construction algorithm is proposed based on multi-source data fusion.The RGB-D sensor was used to obtain 3D structural features in indoor scenes,and the features were then integrated into LiDAR point clouds in the algorithm.Accordingly,an indoor floor plan with 3D structural features was constructed.In the algorithm,images collected by a depth camera in the RGB-D sensor were first converted into pseudo-LiDAR point clouds.Next,a filter based on polynomial function fitting was used to stratify and calibrate the pseudo-LiDAR point clouds,and then the LiDAR and pseudo-LiDAR point clouds were fused.Finally,the fused point cloud data were used to create the indoor 2D floor plan.Experimental results show that the proposed point-cloud hierarchical filtering and calibration method effectively fuses the LiDAR and pseudo-LiDAR point clouds,and the accuracy of the indoor 2D floor plan constructed by the fusion point clouds is significantly improved.
关键词
激光雷达/RGB-D传感器/数据融合/分层过滤/点云校准Key words
LiDAR/RGB-D sensor/data fusion/hierarchical filtering/point cloud calibration引用本文复制引用
基金项目
吉林省自然科学基金(20210101170JC)
出版年
2024
NETL
NSTL
万方数据