IMU-Aided High-Frequency Lidar Odometry for Autonomous Driving

被引:27
|
作者
Xue, Hanzhang [1 ]
Fu, Hao [1 ]
Dai, Bin [1 ,2 ]
机构
[1] Natl Univ Def Technol, Coll Intelligence Sci & Technol, Changsha 410073, Hunan, Peoples R China
[2] Natl Innovat Inst Def Technol, Unmanned Syst Res Ctr, Beijing 100071, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2019年 / 9卷 / 07期
基金
中国国家自然科学基金;
关键词
ego-motion estimation; hand-eye calibration; IMU; lidar odometry; sensor fusion; SCAN REGISTRATION; WORLD;
D O I
10.3390/app9071506
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
For autonomous driving, it is important to obtain precise and high-frequency localization information. This paper proposes a novel method in which the Inertial Measurement Unit (IMU), wheel encoder, and lidar odometry are utilized together to estimate the ego-motion of an unmanned ground vehicle. The IMU is fused with the wheel encoder to obtain the motion prior, and it is involved in three levels of the lidar odometry: Firstly, we use the IMU information to rectify the intra-frame distortion of the lidar scan, which is caused by the vehicle's own movement; secondly, the IMU provides a better initial guess for the lidar odometry; and thirdly, the IMU is fused with the lidar odometry in an Extended Kalman filter framework. In addition, an efficient method for hand-eye calibration between the IMU and the lidar is proposed. To evaluate the performance of our method, extensive experiments are performed and our system can output stable, accurate, and high-frequency localization results in diverse environment without any prior information.
引用
收藏
页数:20
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