Institute of Computing Technology, Chinese Academy IR
Robust Lidar-Inertial Odometry with Ground Condition Perception and Optimization Algorithm for UGV | |
Zhao, Zixu1,2; Zhang, Yucheng1; Shi, Jinglin1; Long, Long1; Lu, Zaiwang1,2 | |
2022-10-01 | |
发表期刊 | SENSORS |
卷号 | 22期号:19页码:19 |
摘要 | Unmanned ground vehicles (UGVs) are making more and more progress in many application scenarios in recent years, such as exploring unknown wild terrain, working in precision agriculture and serving in emergency rescue. Due to the complex ground conditions and changeable surroundings of these unstructured environments, it is challenging for these UGVs to obtain robust and accurate state estimations by using sensor fusion odometry without prior perception and optimization for specific scenarios. In this paper, based on an error-state Kalman filter (ESKF) fusion model, we propose a robust lidar-inertial odometry with a novel ground condition perception and optimization algorithm specifically designed for UGVs. The probability distribution gained from the raw inertial measurement unit (IMU) measurements during a certain time period and the state estimation of ESKF were both utilized to evaluate the flatness of ground conditions in real-time; then, by analyzing the relationship between the current ground condition and the accuracy of the state estimation, the tightly coupled lidar-inertial odometry was dynamically optimized further by adjusting the related parameters of the processing algorithm of the lidar points to obtain robust and accurate ego-motion state estimations of UGVs. The method was validated in various types of environments with changeable ground conditions, and the robustness and accuracy are shown through the consistent accurate state estimation in different ground conditions compared with the state-of-art lidar-inertial odometry systems. |
关键词 | lidar-inertial odometry ground perception state estimation sensor fusion UGV |
DOI | 10.3390/s22197424 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Strategic Priority Research Program of the Chinese Academy of Sciences[XDA28040500] |
WOS研究方向 | Chemistry ; Engineering ; Instruments & Instrumentation |
WOS类目 | Chemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation |
WOS记录号 | WOS:000867193000001 |
出版者 | MDPI |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/19781 |
专题 | 中国科学院计算技术研究所期刊论文 |
通讯作者 | Zhao, Zixu |
作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Zhao, Zixu,Zhang, Yucheng,Shi, Jinglin,et al. Robust Lidar-Inertial Odometry with Ground Condition Perception and Optimization Algorithm for UGV[J]. SENSORS,2022,22(19):19. |
APA | Zhao, Zixu,Zhang, Yucheng,Shi, Jinglin,Long, Long,&Lu, Zaiwang.(2022).Robust Lidar-Inertial Odometry with Ground Condition Perception and Optimization Algorithm for UGV.SENSORS,22(19),19. |
MLA | Zhao, Zixu,et al."Robust Lidar-Inertial Odometry with Ground Condition Perception and Optimization Algorithm for UGV".SENSORS 22.19(2022):19. |
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