面向工业园区无人车的激光建图与定位技术研究

针对工业园区中由于激光SLAM的累计误差造成的建图偏差问题,文章提出了一种基于RTK/全站仪的建图优化技术,利用因子图优化融合多源信息消除前端里程计漂移以获取更精确的位姿信息。另外,文章介绍了一种基于RTK/激光雷达/IMU/里程计的多传感器融合定位技术,以解决工业园区复杂环境下激光点云匹配定位不稳定的问题。论文对所述建图与定位技术进行了工程化实现与验证,试验结果证明了上述技术的有效性。

In order to solve the problem of mapping deviation caused by cumulative error of laser SLAM in industrial park,a mapping optimization technology based on RTK/total station is proposed in this paper.Factor map optimization is used to fuse multi-source information to eliminate front-end odometer drift to obtain more accurate position and attitude information.In addition,this paper introduces a multi-sensor fusion positioning technology based on RTK/LiDAR/IMU/odometer to solve the problem of unstable laser point cloud matching location in the complex environment of industrial park.The engineering implementation and verification of the mapping and positioning technology are carried out in this paper,and the experimental results prove the effectiveness of the above technology.