Cit a tio n fo r fin al p u blis h e d ve r sio n: S a a v e d r a-R uiz, Mi g u el, Pi n t o-Var g a s, An a M a ri a a n d Ro m e r o C a n o, Victo r 2 0 2 2 . M o n o c ul a r vis u al a u t o n o m o u s la n di n g sy s t e m fo r q u a d c o p t e r d r o n e s u si n g s oft w a r e in t h e loo p. IE E E Ae ro s p a c e a n d El e c t r o nic Sy s t e m s M a g a zi n e 3 7 (5) ,

Autonomous landing is a capability that is essential to achieve the full potential of multi-rotor drones in many social and industrial applications. The implementation and testing of this capability on physical platforms is risky and resourceintensive; hence, in order to ensure both a sound design process and a safe deployment, simulations are required before implementing a physical prototype. This paper presents the development of a monocular visual system, using a softwarein-the-loop methodology, that autonomously and efficiently lands a quadcopter drone on a predefined landing pad, thus reducing the risks of the physical testing stage. In addition to ensuring that the autonomous landing system as a whole fulfils the design requirements using a Gazebo-based simulation, our approach provides a tool for safe parameter tuning and design testing prior to physical implementation. Finally, the proposed monocular vision-only approach to landing pad tracking made it possible to effectively implement the system in an F450 quadcopter drone with the standard computational capabilities of an Odroid XU4 embedded processor.