UAV navigation in large-scale GPS-denied bridge environments using fiducial marker-corrected stereo visual-inertial localisation
Feng Wang, Yang Zou, Cheng Zhang, Joao Buzzatto, Minas Liarokapis, Enrique del Rey Castillo, James B.P. Lim
Abstract
The use of Unmanned Aerial Vehicles (UAVs) for bridge inspection has gained popularity recently; however, accurately localising the UAV in GPS-denied areas is still challenging, which hinders the development of fully autonomous UAV-assisted bridge inspection solutions. This paper proposes a fiducial marker-corrected stereo visual-inertial localisation (FMC-SVIL) method, running on a resource-constrained onboard computer, to estimate UAV's global pose underneath bridge girders. The proposed FMC-SVIL utilises an optimised stereo visual-inertial odometry for continuous relative pose estimation between consecutive camera frames and an improved AprilTag2-based measurement algorithm for accurate global referencing and periodic pose corrections. The method is validated through extensive experiments, and the results show that the FMC-SVIL achieved UAV localisation with a root mean square error of 0.416 m in sunny conditions and 0.340 m in cloudy conditions. FMC-SVIL outperforms the leading vision-based simultaneous localisation and mapping (SLAM) algorithms for flights over multiple bridge spans.