Robust localization is critical for the navigation and control of mobile robots. Global Navigation Satellite Systems (GNSS), Visual-Inertial Odometry (VIO), and Simultaneous Localization and Mapping (SLAM) offer different methods for achieving this goal. In some cases however, these methods may not be available or provide high enough accuracy. In such cases, these methods may be augmented or replaced with fiducial marker pose estimation. Fiducial markers can increase the accuracy and robustness of a localization system by providing an easily recognizable feature with embedded fault detection. This paper presents an overview of fiducial markers developed in the recent years and an experimental comparison of the four markers (ARTag, AprilTag, ArUco, and STag) that represent the state-of-the-art and most widely used packages. These markers are evaluated on their accuracy, detection rate and computational cost in several scenarios that include simulated noise from shadows and motion blur. Different marker configurations, including single markers, planar and non-planar bundles and multi-sized marker bundles are also considered in this work.

强大的本地化对于移动机器人的导航和控制至关重要。全球导航卫星系统（GNSS），视觉惯性里程表（VIO）以及同时定位和制图（SLAM）提供了实现此目标的不同方法。但是，在某些情况下，这些方法可能不可用或不够准确。在这种情况下，可以用基准标记位姿估计来增强或替换这些方法。基准标记通过提供易于识别的嵌入式故障检测功能，可以提高定位系统的准确性和鲁棒性。本文概述了近年来开发的基准标记，并对代表最新技术和使用最广泛的四种标记（ARTag，AprilTag，ArUco和STag）进行了实验比较。在几种情况下，包括阴影和运动模糊产生的模拟噪声，会对这些标记的准确性，检测率和计算成本进行评估。在这项工作中还考虑了不同的标记配置，包括单个标记，平面和非平面束以及多尺寸标记束。