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 Cups (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 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 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 Runs 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.