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	Visual-Inertial Odometry Tightly Coupled with Wheel Encoder Adopting Robust Initialization and Online Extrinsic Calibration
	Liu, Jinxu1,2; Gao, Wei1,2; Hu, Zhanyi1,2
	2019-11-04
会议日期	2019年11月4日至8日
会议地点	中国澳门
英文摘要	Combining camera, IMU and wheel encoder is a wise choice for car positioning because of the low cost and complementarity of the sensors. We propose a novel extended visual-inertial odometry algorithm tightly fusing data from the above three sensors. Firstly we propose an IMU-odometer pre-integration approach utilizing complete IMU measurements  and wheel encoder readings, to make scale estimation more  accurate in subsequent 4-degrees of freedom(DoF) optimization. Secondly we develop an original initialization module where  encoder readings are fully utilized to refifine gravity direction and provide an initial value for camera pose in real scale.  Thirdly, we design a computationally effificient online extrinsic calibration method by fifixing the linearization point for the rotational component of IMU-odometer extrinsic parameters, which is deployed depending on the convergence of accelerometer bias. Experimental results prove the robustness of our initialization module and the accuracy of the whole trajectory, as well as the improvement brought about by online extrinsic calibration. Our program can also run on an Nvidia Jetson TX2 module in real time.
会议录出版者	IEEE
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/44971]
专题	自动化研究所_模式识别国家重点实验室_机器人视觉团队
通讯作者	Gao, Wei
作者单位	1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences
推荐引用方式 GB/T 7714	Liu, Jinxu,Gao, Wei,Hu, Zhanyi. Visual-Inertial Odometry Tightly Coupled with Wheel Encoder Adopting Robust Initialization and Online Extrinsic Calibration[C]. 见:. 中国澳门. 2019年11月4日至8日.

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