Simple Vision Markers for Reliable Drone Landing in Robotics Workflows

Abstract

This paper investigates low-complexity visual markers for autonomous drone landing exercises in introductory robotics courses. The author tested marker size, contrast, and border thickness using a simulated camera pipeline and indoor quadcopter trials. A high-contrast concentric-square marker reduced average landing error by 27% compared with common QR-pattern references while requiring less processing time. The method is intended for beginner-friendly robotics labs with limited hardware resources.