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Laser SLAM Pose Optimization Algorithm Based on Graph Optimization Theory and GNSS

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提出一种激光雷达SLAM(simultaneous localization and mapping)位姿优化算法。该算法基于图优化算法理论并融合GNSS (global navigation satellite system)数据,在位姿图中加入卫星定位节点,可以有效将无回环时轨迹误差控制在GNSS定位误差范围内,有长时性回环时可以准确定位回环检测点,从而达到提高激光雷达SLAM位姿全局一致性的效果。在室外刚性特性较好的城市环境和刚性特性较差的非城市环境下进行测试,从结果可以看出:所提算法将在无回环300 m距离直线建图情况以及在360 m以上距离一次、二次回环情况下的轨迹偏差分别控制在1 m左右、0.2 m以内以及0.1 m左右,这充分证明了所提算法的有效性。


In this paper, a LiDAR simultaneous localization and mapping (SLAM) pose optimization algorithm is proposed based on graph optimization theory and global navigation satellite system (GNSS) data. By adding the satellite positioning node into the pose graph, the trajectory error can be effectively controlled within the range of GNSS positioning error when there is no loopback. In long distance loopback, the loopback detection point can be accurately located, which improves the global consistency of the LiDAR SLAM pose graph. The proposed algorithm is tested in the urban environment with better rigidity and in the non-urban environment with weaker rigidity. Experimental results show that the trajectory drift can be controlled to be about 1 m for 300 m straight-line mapping when there is no loopback. In the case of long distance (above 360 m) loopback, the proposed algorithm controls the trajectory drift to be within 0.2 m and about 0.1 m for the primary and the secondary loopback,respectively. These results fully demonstrate the effectiveness of the proposed algorithm.








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陆世东:湖北省国土资源研究院, 湖北 武汉 430071
涂美义:湖北省国土资源研究院, 湖北 武汉 430071
罗小勇:湖南格纳微信息科技有限公司, 湖南 长沙 410006
郭超:湖南格纳微信息科技有限公司, 湖南 长沙 410006


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Lu Shidong,Tu Meiyi,Luo Xiaoyong,Guo Chao. Laser SLAM Pose Optimization Algorithm Based on Graph Optimization Theory and GNSS[J]. Laser & Optoelectronics Progress, 2020, 57(8): 081024

陆世东,涂美义,罗小勇,郭超. 基于图优化理论和GNSS激光SLAM位姿优化算法[J]. 激光与光电子学进展, 2020, 57(8): 081024

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