关键词: 即时定位与地图构建（SLAM）, 惯性测量单元（IMU）, 关键帧, 非线性优化, 闭环检测, 重定位

Abstract:

Aiming at solving the problem that the accuracy and robustness of the current visual-inertial simultaneous localization and mapping (SLAM) algorithm are not high due to lack of the loop-closing detection, this paper presents a keyframe-based visual-inertial SLAM algorithm for monocular and stereo cameras. The visual-inertial SLAM system provides locally consistent trajectory through a visual-inertial odometry. Then the global consistent trajectory is achieved through loop-closing detection and non-linear optimization in parallel, thus a continuous global map is    created. Moreover, this algorithm has the ability to perform relocations in a map that has been obtained and to       continue the subsequent building. The experiments are carried out using the EuRoC dataset to evaluate the accuracy, relocalization and run time of the algorithm. Experiment results show that, compared with the current visual-inertial SLAM algorithm, the proposed method can reduce error accumulation and the drift, relocate the camera and continue to build the map on the basis of the previous map.

Key words: simultaneous localization and mapping (SLAM), inertial measurement unit (IMU), keyframe, non-linear optimization, loop-closing detection, relocalization