Drones Take Flight
Engineering a fully autonomous drone
is rife with challenges—particularly in
busy and complex urban areas.
First, they are not like the autonomous vehicles that operate on land.
UAVs have extreme space and weight
restrictions. Whereas a car can potentially have dozens, even hundreds, of
sensors mounted across its surface, a
drone can accommodate the weight
of only a few.
Second, UAVs move in almost every
direction in a three-dimensional (3D)
space, while a motor vehicle operates on
a two-dimensional plane. This makes
designing software and algorithms for
UAVs exponentially more complex.
Finally, the simple fact these machines are suspended in the air and
constantly moving introduces additional challenges and risks.
Today, most UAVs operate on a
line-of-sight basis. Essentially, a person uses a transmitter, typically operating in the 2.4GHz frequency band,
AS DRONES HAVE matured into smarter and more practical machines, they have hummed, buzzed, and whirred their way
into industries as diverse as movie
production, agriculture, civil engineering, and insurance. It is entirely
clear that autonomous drones will
play a prominent role in business
in the coming years. Firms such as
Amazon, FedEx, and Uber have experimented with the technology to
deliver packages, food, and more,
while military agencies, emergency
responders, gaming companies, entertainment firms, and others have
explored other possibilities.
“Drones introduce far more efficient ways to accomplish some tasks,”
says Todd Curtis, president of Airsafe.
com, a site that tracks drone and other
Powering more advanced drones
are more sophisticated on-board sensors and processors, better artificial
intelligence (AI) algorithms, and more
advanced controllers and communication systems. In addition, engineers
are packing greater numbers of sensors into drones—and using them in
different combinations—to create
greater “awareness” of the surrounding environment. This sensing, when
combined with GPS and other navigation capabilities, allows drones to tackle more advanced autonomous tasks,
including devices that explore caverns
or other hard-to-reach spaces, as well
as underwater drones that conduct research by scanning oceans.
Yet, despite rapidly evolving capa-
bilities, it also is clear that autono-
mous drones have not completely
mastered the art and science of navi-
gating and accomplishing their des-
ignated task. Buildings, birds, power
lines, trees and people remain formi-
dable obstacles for autonomous Un-
manned Aerial Vehicles (UAVs), as they
are known. Fog, snow, smoke, and dust
present additional challenges.
It is one thing to showcase a drone
in a controlled environment; it is quite
another to have it operate flawlessly in
the wild. UAVs must have near-perfect
vision and sensing, as well as the ability to navigate areas where satellite and
communications signals cannot reach
and need backup and fail-safe systems
that can take control of the drone if/
when something goes astray.
“We are seeing remarkable advances
in onboard sensing and processing,
but also the use of far more sophisticated AI (artificial intelligence) algorithms in drones,” says Nathan Michael,
associate research professor at the
Robotics Institute of Carnegie Mellon
University. “These navigation and control systems are moving drones beyond the basic ability to fly from
Point A to Point B. They’re making it
possible for drones to understand
the world around them and make
complex decisions in real time.”
When Drones Fly
Drone technology is poised to enter the mainstream of business
and society, but engineering robust controls remains a challenge.
Technology | DOI: 10.1145/3360913 Samuel Greengard