Improving the perception of visual fiducial markers in the field using
  Adaptive Active Exposure Control
Ziang Ren Samuel Lensgraf Alberto Quattrini Li
Accurate localization is fundamental for autonomous underwater vehicles
(AUVs) to carry out precise tasks, such as manipulation and construction.
Vision-based solutions using fiducial marker are promising, but extremely
challenging underwater because of harsh lighting condition underwater. This
paper introduces a gradient-based active camera exposure control method to
tackle sharp lighting variations during image acquisition, which can establish
better foundation for subsequent image enhancement procedures. Considering a
typical scenario for underwater operations where visual tags are used, we
proposed several experiments comparing our method with other state-of-the-art
exposure control method including Active Exposure Control (AEC) and
Gradient-based Exposure Control (GEC). Results show a significant improvement
in the accuracy of robot localization. This method is an important component
that can be used in visual-based state estimation pipeline to improve the
overall localization accuracy.