IMU-Aided High-Frequency Lidar Odometry for Autonomous Driving
AbstractFor 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. View Full-Text
Share & Cite This Article
Xue, H.; Fu, H.; Dai, B. IMU-Aided High-Frequency Lidar Odometry for Autonomous Driving. Appl. Sci. 2019, 9, 1506.
Xue H, Fu H, Dai B. IMU-Aided High-Frequency Lidar Odometry for Autonomous Driving. Applied Sciences. 2019; 9(7):1506.Chicago/Turabian Style
Xue, Hanzhang; Fu, Hao; Dai, Bin. 2019. "IMU-Aided High-Frequency Lidar Odometry for Autonomous Driving." Appl. Sci. 9, no. 7: 1506.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.