Stereo vision and UWB-based multisensor fusion SLAM

Tongyang Li; Yuqi Huang

doi:10.1117/12.3052925

3 January 2025 Stereo vision and UWB-based multisensor fusion SLAM

Tongyang Li, Yuqi Huang

Author Affiliations +

Proceedings Volume 13442, Fifth International Conference on Signal Processing and Computer Science (SPCS 2024); 134421C (2025) https://doi.org/10.1117/12.3052925
Event: Fifth International Conference on Signal Processing and Computer Science (SPCS 2024), 2024, Kaifeng, China

Abstract

Accurate and robust localization is crucial for indoor mobile robots, where traditional vision-based systems often struggle with precision and reliability. This paper presents a SLAM/UWB fusion localization algorithm designed to overcome these challenges. By building on the ORB-SLAM3 stereo-inertial framework and integrating Ultra-Wideband (UWB) positioning data using an Extended Kalman Filter (EKF), the method introduces time and distance thresholds to filter outliers and improve data accuracy. Experimental results show that this approach outperforms ORB-SLAM3 stereo visual-inertial localization, achieving superior positioning accuracy and enhanced robustness in both the Euroc dataset and real-world indoor environments.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tongyang Li and Yuqi Huang "Stereo vision and UWB-based multisensor fusion SLAM", Proc. SPIE 13442, Fifth International Conference on Signal Processing and Computer Science (SPCS 2024), 134421C (3 January 2025); https://doi.org/10.1117/12.3052925

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