AprilTags 3D: Dynamic Fiducial Markers for Robust Pose Estimation in Highly Reflective Environments and Indirect Communication in Swarm Robotics
This addresses the challenge of robust pose estimation for swarm robotics in noisy, real-world conditions, representing an incremental improvement over existing marker systems.
The paper tackles the problem of inaccurate pose estimation with fiducial markers in field robotics, especially in reflective environments, by introducing AprilTags3D, a method that adds a third dimension to marker detection using only RGB sensors, resulting in improved accuracy for swarm robotic applications like boat latching and formations.
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.