Recursive ArUco Markers: A Scalable Fiducial Marker Design for Unmanned Aerial Vehicle Landing Pads

2026-07-15

AI Summary

This work addresses the limitations of conventional ArUco markers, which suffer from poor detectability at extreme distances and high susceptibility to occlusion due to their reliance on a visible central region in recursive designs. To overcome these challenges, the authors propose a novel recursive ArUco marker that embeds complete child markers within the black-and-white bits of parent markers and employs an enhanced bit-sampling strategy. This design enables recursive nesting at arbitrary depths while ensuring consistent multi-scale detection, all without requiring visibility of the central region. The resulting marker maintains a single unique identifier and exhibits strong robustness against occlusion. Experimental results demonstrate that the proposed approach significantly extends the effective operational range and enhances occlusion resilience, offering a scalable, high-precision landing guidance solution for large-scale drone swarms.

Abstract

Unmanned Aerial Vehicles (UAVs) increasingly rely on visual fiducial markers for autonomous navigation and precision landing. However, standard markers suffer from limited operational ranges, becoming undetectable when the camera is either too far or too close. While recursive and fractal markers have been proposed to address this issue, existing approaches either require the marker's center to remain visible, making them vulnerable to occlusion, or are limited in their recursion depth and placement. We propose a novel Recursive ArUco marker design. Our method allows any standard fiducial marker to be transformed into a recursive marker with an arbitrary depth. By employing a modified bit-sampling strategy during detection, we embed complete markers within both the black and white bits of the parent marker. This approach guarantees unlimited recursion depth and robust detection even with partial occlusion, as it does not rely on the marker's center being visible. Furthermore, by maintaining a single, unique identifier across all recursive scales, our proposal provides an extensive dictionary of multiple unique landing pads. This capability allows fleets of UAVs to operate simultaneously, with each drone landing at its designated location -- a feature not supported by existing Fractal and Harco markers due to their structural and dictionary constraints.

Problem

• fiducial markers
• UAV landing
• occlusion robustness
• scalable detection
• multi-UAV coordination

Innovation

• Recursive ArUco
• fiducial marker
• occlusion-robust detection
• multi-scale landing pad
• UAV precision landing