Closed-form integration of IMU error state covariance for optimization-based Visual-Inertial State Estimator
作者单位：School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System
会议名称：《第三十九届中国控制会议》
会议日期：2020年
学科分类：08[工学] 081105[工学-导航、制导与控制] 082503[工学-航空宇航制造工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程]
关 键 词：visual-inertial state estimator pre-integration
摘 要：In this paper, we propose a closed-form IMU error state covariance integration method for optimization-based visualinertial state estimator. We derive a closed-form solutions of the IMU error state covariance propagation in pre-integration process, yielding improved accuracy of IMU residual information matrix. Our visual-inertial state estimator is based on a tightly-coupled, sliding-window optimization framework, which jointly estimate the IMU states and landmarks and performing marginalization to limit the computational cost. Finally, the system are validated in park environment dataset, the result shows our proposed method is effective.