  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 resource-intensive; 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 software-in-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.
