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Accurate camera pose estimation result is essential for visual SLAM (VSLAM).This paper presents a novel pose correction method to improve the accuracy ofthe VSLAM system. Firstly, the relationship between the camera pose estimationerror and bias values of map points is derived based on the optimized functionin VSLAM. Secondly, the bias value of the map point is calculated by astatistical method. Finally, the camera pose estimation error is compensatedaccording to the first derived relationship. After the pose correction,procedures of the original system, such as the bundle adjustment (BA)optimization, can be executed as before. Compared with existing methods, ouralgorithm is compact and effective and can be easily generalized to differentVSLAM systems. Additionally, the robustness to system noise of our method isbetter than feature selection methods, due to all original system informationis preserved in our algorithm while only a subset is employed in the latter.Experimental results on benchmark datasets show that our approach leads toconsiderable improvements over state-of-the-art algorithms for absolute poseestimation.

Camera Pose Correction in SLAM Based on Bias Values of Map Points