Abstract
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.
Abstract (translated)
准确的局部定位对于自主水下车辆（AUVs）执行精确任务（如操作和建设）至关重要。使用标记引导的视觉解决方案前景广阔，但在水下由于恶劣的照明条件而变得极其困难。本文介绍了一种基于梯度的主动相机曝光控制方法，以解决图像采集期间图像锐利的照明变化，为后续图像增强过程奠定更好的基础。考虑到水下操作中通常使用视觉标签的情况，我们提出了几种实验，将我们的方法与其他最先进的曝光控制方法（包括主动曝光控制（AEC）和基于梯度的曝光控制（GEC））进行比较。结果表明，机器人的局部定位精度得到了显著提高。这种方法是用于视觉 based 状态估计管道以提高整体局部定位精度的关键组成部分。
URL
https://arxiv.org/abs/2404.12055
