论文标题
APRILTAGS 3D：在高度反射性环境中稳健姿势估计的动态基金标记和群体机器人的间接通信
AprilTags 3D: Dynamic Fiducial Markers for Robust Pose Estimation in Highly Reflective Environments and Indirect Communication in Swarm Robotics
论文作者
论文摘要
尽管基准标记在实验室条件下具有准确的姿势估计，但是在控制嘈杂因素的情况下，在现场机器人应用中使用它们仍然是一个挑战。这仅限于基准制造商系统，因为它们仅在RGB图像空间内工作。结果，图像中的噪声会产生较大的姿势估计误差。在机器人应用中，基准标记主要以其原始和简单形式使用，用作印刷纸板中的平面。此设置足以用于基本的视觉致暗销和增强现实应用程序，但不适合复杂的群体机器人应用程序，其中设置由多个动态标记组成（LCD屏幕上显示的标记）。本文描述了一种名为Apriltags3d的新方法，该方法通过在标记探测器中添加第三维来提高现场机器人技术中APRILTAGS的姿势估计精度。此外，还提出了实验结果，该结果应用了提出的方法来群自动机器人船与它们之间的闩锁和创建机器人形成。
Although fiducial markers give an accurate pose estimation in laboratory conditions, where the noisy factors are controlled, using them in field robotic applications remains a challenge. This is constrained to the fiducial maker systems, since they only work within the RGB image space. As a result, noises in the image produce large pose estimation errors. In robotic applications, fiducial markers have been mainly used in its original and simple form, as a plane in a printed paper sheet. This setup is sufficient for basic visual servoing and augmented reality applications, but not for complex swarm robotic applications in which the setup consists of multiple dynamic markers (tags displayed on LCD screen). This paper describes a novel methodology, called AprilTags3D, that improves pose estimation accuracy of AprilTags in field robotics with only RGB sensor by adding a third dimension to the marker detector. Also, presents experimental results from applying the proposed methodology to swarm autonomous robotic boats for latching between them and for creating robotic formations.
