The developing and application of graph optimization-based GNSS/stereo visual/inertial SLAM system

被引：0
|
作者：
Xia L. [1 ]
Song Z. [1 ]
Fang L. [1 ]
Sun W. [2 ]
机构：
[1] School of Automation Engineering, Northeast Electric Power University, Jilin
[2] School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin
来源：
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | 2024年 / 32卷 / 05期
关键词：
global observation; GNSS/stereo visual/inertial SLAM system; graph optimization; line feature constraint; multi-sensor fusion;
D O I：
10.13695/j.cnki.12-1222/o3.2024.05.008
中图分类号：
学科分类号：
摘要：
In order to improve the outdoor long-endurance positioning accuracy of robots, the developing and application of graph optimization-based global navigation satellite system (GNSS)/stereo visual/inertial simultaneous localization and mapping (SLAM) system is proposed. As the extra geometrical constraints, the spatial line features are integrated into the threads of the front-end feature extraction and back-end pose optimization to enhance the pose estimates. At the same time, the graph structure for joint optimization is constructed via factor graphs and the global observation error model is further derived. The nearly 200-meter-long BullDog-CX robot substation experiment shows that compared with VINS-Fusion and PL-VINS, the proposed algorithm has achieved about 12.6% and 3.4% improvement in positioning accuracy, which provides a feasible scheme for long-endurance navigation of outdoor robots. © 2024 Editorial Department of Journal of Chinese Inertial Technology. All rights reserved.
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页码：475 / 483
页数：8
相关论文
共 18 条
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