RainbowTag: a Fiducial Marker System with a New Color Segmentation Algorithm

We introduce a new color-based fiducial marker system-RainbowTag (RT)-for detection and identification that is suitable for autonomous navigation due to robustness to varying lighting conditions, motion blur, partial occlusion and folding. This system uses cameras already present on the vehicles to complement spatial information estimated from other sensors (e.g., Global Positioning System, inertial measurement, radar). RT is composed of a fiducial marker design and its adapted detection algorithm. Numerous real-world experiments demonstrate that markers can be reliably detected in various lighting conditions, in the presence of large motion blur, and even when folded or partially occluded. In all test conditions, RT outperforms the fiducial markers Aruco and ChromaTag. Compared to other blur-resistant fiducials that are circularly symmetric [1], [2], RT has the advantage that it encodes orientation information. Our detection algorithm is powered by a novel color segmentation approach that carefully orchestrates information from the hue constant IPT, the perceptually uniform CIELAB, and the Bradford LMS cone response color spaces.