TS-LCD: Two-Stage Loop-Closure Detection Based on Heterogeneous Data Fusion

TS-LCD: Two-Stage Loop-Closure Detection Based on Heterogeneous Data Fusion

Blog Article

Loop-closure detection plays a pivotal role in simultaneous localization and mapping (SLAM).It serves to minimize cumulative errors and ensure the overall consistency of the generated map.This paper introduces a multi-sensor fusion-based loop-closure detection scheme (TS-LCD) to address the challenges of low robustness and inaccurate loop-closure detection encountered in single-sensor systems under varying lighting conditions and #4 MEDIUM BROWN structurally similar environments.Our method comprises two innovative components: a timestamp synchronization method based on data processing and interpolation, and a two-order loop-closure detection scheme based on the fusion validation of visual and laser loops.

Experimental Rolling Pins results on the publicly available KITTI dataset reveal that the proposed method outperforms baseline algorithms, achieving a significant average reduction of 2.76% in the trajectory error (TE) and a notable decrease of 1.381 m per 100 m in the relative error (RE).Furthermore, it boosts loop-closure detection efficiency by an average of 15.

5%, thereby effectively enhancing the positioning accuracy of odometry.