Design and Research of AGV Indoor Positioning System Based on Visual and Ultra Wideband Combination Positioning

Abstract

Aiming at the problems of cumulative error in monocular visual positioning and Non-Line-of-Sight (NLOS) error in UWB positioning for the automated guided vehicle (AGV) in indoor environments, a combined method of vision and Ultra-Wide Band (UWB) is proposed for indoor AGV positioning. Firstly, the overall structure and system of the AGV are designed to achieve indoor navigation and positioning functions. Secondly, the monocular visual and UWB positioning data are fused using the Error State-Extended Kalman Filter algorithm (ES-EKF) to obtain the optimal pose estimation of the AGV. Finally, the AGV is used as a mobile platform to conduct positioning experiments in different indoor environments. The experimental results demonstrate that the navigation and positioning system has high accuracy and robustness in indoor environments with obstacles, and no significant drift or discontinuity phenomena occur during the positioning process, indicating its practicality in indoor settings.