Loosely-Coupled Ultra-wideband-Aided Scale Correction for Monocular Visual Odometry
Thien Hoang Nguyen, Thien‐Minh Nguyen, Muqing Cao, Lihua Xie
Abstract
In this paper, we propose a method to address the problem of scale uncertainty in monocular visual odometry (VO), which includes scale ambiguity and scale drift, using distance measurements from a single ultra-wideband (UWB) anchor. A variant of Levenberg–Marquardt (LM) nonlinear least squares regression method is proposed to rectify unscaled position data from monocular odometry with 1D point-to-point distance measurements. As a loosely-coupled approach, our method is flexible in that each input block can be replaced with one’s preferred choices for monocular odometry/SLAM algorithm and UWB sensor. Furthermore, we do not require the location of the UWB anchor as prior knowledge and will estimate both scale and anchor location simultaneously. However, it is noted that a good initial guess for anchor position can result in more accurate scale estimation. The performance of our method is compared with state-of-the-art on both public datasets and real-life experiments.