Aerospace and Electronic Systems Magazine July 2017 - 58

Student Research Highlight:

DOI. No. 10.1109/MAES.2017.160192

Embedded Platform for UAS Obstacle and Landing Path
Detection-PERSEO
Umberto Papa, University of Naples "Parthenope," Naples, Italy

For the PERSEO system, I am improving three types of sensors:

INTRODUCTION
The PERSEO (Piattaforma Embedded per la Ricerca del Sentiero
di Atterraggio ed Ostacoli-Embedded Platform for Obstacle and
Landing Path Detection) system is my Ph.D. research theme. Specifically, the idea and main research focus are the design and development of an embedded electronic platform that will be installed
on an unmanned aircraft system (UAS) for attitude control and
obstacle detection. The aim is to calculate and extract the landing
path and detect obstacles that surround the unmanned aircraft. The
sensors onboard the main platform must have these key specifications: low cost, miniature size, robustness, and fast response time.
It is important to improve UAS, because these types of vehicles
are much used in scientific, military and civil applications (climate
research, precision farming, search and rescue, disaster assessment, inspection of electrical power lines, urban traffic monitoring,
three-dimensional mapping, etc.). The research focuses on the design and development of an embedded electronic platform that aids
the aerial vehicle during navigation, in particular during landing. A
bouquet of low-cost sensors was utilized for the PERSEO system.
Each sensor was tested on a quadrotor, considering a landing vertical distance from 10 to 150 cm. The applied technologies (sensors and controllers) change every day because of miniaturization
processes and the development of new materials. Recent research
studies focused on the development of numerical algorithms for
sensor data fusion to improve mainly the numerical processes and
rarely the items' costs. With the advent of miniaturized and lowcost sensors, attention has returned to the sensors' capabilities and
performance. It is clear that for UAS (as for any other aerial platform), a fundamental task is saving weight, together with low-cost
issues.

STUDENT CONTRIBUTION
My contribution enhances the low-cost and miniaturization processes through a single-sensor analysis and finally a merge of all
sensors.
Author's current address: Department of Science and Technology, University of Naples "Parthenope," Is. C4, 80143, Naples,
Italy, E-mail: (umberto.papa@uniparthenope.it).
Manuscript received November 5, 2016, revised November 7,
2016, and ready for publication January 4, 2017.
Review handled by J. Glass.
0885/8985/17/$26.00 © 2017 IEEE
58

Sonic Ranger sensors (SRSs)

Infrared sensors (IRSs)

Optical sensors (OPSs)

All sensors compose the PERSEO system, aiding a small
quadrotor in the landing procedure by giving real-time position
and attitude information from a fixed surface (ground).
Why quadrotor? Among vertical takeoff and landing (VTOL)
aircraft, such as conventional helicopters, crafts with rotors like
the tilt-rotor, and fixed-wing aircrafts with directed jet thrust
capability, the quadrotor, or quadcopter (a helicopter with four
rotors fixed on the ends of a cross-shaped frame), is frequently
chosen, especially in academic research on miniature or microsize UASs, as an effective alternative to the high cost and complexity of conventional rotorcrafts because of its ability to hover
and move without the complex system of linkages and blade elements present in a standard single-rotor vehicle. First, it is necessary to know how the sensors work [2] and how the atmospheric
conditions and the magnetic flow influence each sensor. The SRS
performance was evaluated in [2]. A temperature, pressure, and
relative humidity analysis was done [3] because of the use of a
climatic chamber and considering the speed of sound a equation
in classical mechanics:

a= K

(1)

where K is the modulus of the bulk elasticity of a gas obtained
with the multiplication of the adiabatic index γ and the pressure p,
while ρ is the density. If we use the ideal gas law to replace p with
nRT/V, and replace ρ with nM/V, the speed of sound for an ideal
gas (aideal) is
( γ RT ) 
aideal = 
M



= m s 

(2)

where R is the molar gas constant (approximately 8.3145 J/mol·K),
T (K) is the absolute temperature, and Mair (kg/mol) is the molar
mass of the gas (for dry air, M is about 0.029 kg/mol).

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JULY 2017

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