Enhanced Visual Loop Closing for Laser-Based SLAM

Zulun Zhu, Shaowu Yang, Huadong Dai

Abstract: Three-dimensional (3D) laser-based simultaneous localization and mapping (SLAM) can provide real-time pose information and construct accurate 3D map. However, detecting loop closures is a challenging task in the 3D laser-based SLAM because of the heavy computational overheads. In this paper, we propose a visual method to simultaneously detect and correct loop closures in the 3D laser-based SLAM based on prior work. In particular, we improve the experiments and evaluate our method by analyzing computational errors. The experimental results on the KITTI dataset prove that our method can efficiently reduce motion accumulation errors and successfully ensure the consistency performance of loop closure correction.