IEEE - Aerospace and Electronic Systems - May 2022 - Tutorial XV - 2

Tutorial:
DOI. No. 10.1109/MAES.2021.3115208
Monocular Visual Autonomous Landing System for
Quadcopter Drones Using Software in the Loop
Miguel Saavedra-Ruiz, Ana Maria Pinto-Vargas, and Victor Romero-Cano,
Universidad Autonoma de Occidente, Santiago de Cali 760030, Colombia
Autonomous landing is a capability that is essential to
achieve the full potential of multirotor 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 beforeimplementingaphysical
prototype. This article 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 aGazebobased
simulation, our approach provides a tool for safe
parameter tuning and design testing prior to physical
implementation. Finally, the proposed monocular visiononly
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.
INTRODUCTION
Unmanned aerial vehicles (UAVs) have recently become
popular due to their potential in terms of performing complex
tasks such as infrastructure inspection [1], target detection
[2], [3], or search and rescue [4]. The use of these
gadgets has led to both substantial improvements in the
Authors' current address: Miguel Saavedra-Ruiz is
with Mila-Quebec Institute of Artificial Intelligence,
Universite de Montreal, Quebec H3T 1J4, Canada;
Ana Maria Pinto-Vargas is with Alternova Tech SAS,
Medellı´n 050022, Colombia; Victor Romero-Cano is
with the Faculty of Engineering, Universidad Auto´noma
de Occidente, Santiago de Cali 760030, Colombia
(e-mail: miguel.angel.saavedra.ruiz@umontreal.ca;
ana.pinto@alternova.io; varomero@uao.edu.co).
Manuscript received July 26, 2020, revised May 24,
2021; accepted August 9, 2021.
Review handled by Giancarmine Fasano.
0885-8985/21/$26.00 ß 2021 IEEE
2
efficiency ofthese processes and a reduction in human casualties
while performing hazardous labors. The deployment
of UAVs in such applications requires a complete suite of
sensors such as GPS, laser rangefinders, radar, and cameras
[5], which can be used to endow the vehicle with environmental
awareness and the capability to perceive events
ofinterest. However, the use ofmany peripherals in a UAV
requires an extensive amount of on-board computational
resources and power that are not always available owing to
the vehicle's dimensions and the high implementation costs.
Cameras have been proposed as a feasible alternative to
overcome these issues, as they have a relative low price and
enable the estimation of content-rich representations of the
environment. For instance, cameras have been widely
employed in various tasks such as mapping [6] and object
tracking [7]. Further research efforts have been conducted to
make use of cameras in the development of visual-based
autonomous landing systems for UAVs. Autonomous landing
maneuvers remain a crucial task for rotorcraft, and allow
the development of complete, end-to-end autonomous flying
vehicles that are capable ofperforming complex assignments
such as those mentioned above.
Most state-of-the-art visual-based landing systems
have shown unprecedented results that are comparable to
the performance ofUAVs with a full suite of sensors [10].
The employment of natural landmarks to land a rotorcraft
in unstructured environments is a strategy commonly used
for emergency landing situation [6], [11]. These methods
rely on the use of vision-based SLAM algorithms such as
ORB_SLAM2 [12] for localization ofthe vehicle and mapping
of appropriate landing spots in the environment. Nevertheless,
these techniques are prone to deliver low spatial
resolution and be computationally expensive, hindering the
performance ofautonomous landing applications.
On the other hand, the utilization of artificial landmarks
is one of the most traditional techniques used in
landings on both static [13] and moving platforms [14].
The extraction of information from a landmark, such as
the relative pose or template coordinates, is broadly used
in the application of image-based visual servoing (IBVS),
a technique that performs the majority of the control calculations
in 2D image space [15] and reduces the computational
load of a small rotorcraft while landing.
IEEE A&E SYSTEMS MAGAZINE
MAY 2022
IEEE - Aerospace and Electronic Systems - May 2022 - Tutorial XV

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