IEEE Robotics & Automation Magazine - June 2015 - 25

Automation of Aerial Robotics
The price-performance ratio of processors, sensors, and networking infrastructure, which has dropped significantly over the
last decade, has led to new applications founded on the convergence of computation, sensing, and computing. A recent
General Electric report [1] calls this convergence the industrial
Internet and suggests that the potential macroeconomic benefit
from the industrial Internet could be comparable with the economic productivity gain attributable to the Internet revolution of
the late 20th century. Others call it the Internet of Things and
predict an economic impact in the tens of trillions of dollars [2].
More than 75% of business leaders surveyed predicted a direct
impact of this technology on their business [3]. This convergence also holds great promise for automation with robots,
which "emphasizes efficiency, productivity, quality, and reliability, focusing on systems that operate autonomously, often in
structured environments over extended periods" [4].
In this article, we address this confluence of technologies
enabling automation in the context of aerial robotics, a field that
has also seen dramatic advances over the last decade. The same
drop in price-performance ratio of processors and sensors has fueled the development of micro unmanned aerial vehicles (UAVs)
that are between 0.1 and 1 m in length and 0.1-2 kg in mass.
These low-cost platforms are easy to manufacture in contrast to
the expensive UAVs used for military applications. The number of
Predators and Global Hawks is estimated to be around 1,000.
Growth in the consumer electronics industry (millions or billions
of components at low cost) has resulted in inexpensive hardware
for sensing and computation. These advances, coupled with opensource tools for building robots like quadrotors [5], have led to innovative low-cost toys and hobby kits (e.g., diydrones.org). The
real opportunity for robotics and automation is in leveraging these
tools (and the convergence of computation, sensing, and communication) to develop economical (compared with the military
counterparts), functional, and robust aerial robots. These can be
used in such tasks as inspection [6], interaction with the environment [7], [8], search and rescue [9], construction [10], [11], and
mapping of homes and offices.
Early quadrotor vehicles were primarily experimental systems, but improved design and software tools have lead to significant increases in reliability and reductions in cost. Today,
quadrotors have reached the maturity of consumer-grade devices. To reiterate, this is in large part due to the decreasing price-
performance ratio of sensors for autonomous navigation,
including global positioning systems (GPSs), cameras, IMUs,
and laser scanners [7], [12]-[16]. In this context, low-cost range
sensors offer an attractive alternative to high-end laser scanners
and 3-D cameras for applications such as indoor navigation and
mapping, surveillance, and autonomous robotics.
Consumer-grade range sensing technology has led to many
devices becoming available on the market, like the Microsoft
Kinect sensor and the ASUS Xtion sensor (PrimeSense 2010;
see Figure 1). The richness of the provided data and the low
cost of the sensor have attracted many researchers from the
fields of mapping, 3-D modeling, and reconstruction. The
ASUS Xtion sensor boasts a lower weight than the first

(a)

(b)
Figure 1. The flying platform (a) back view and (b) front view.

generation of red, green, blue, and depth (RGB-D) cameras
(around 70 g without the external casing). (While this specific
sensor is no longer available, there are others under development that are likely to be available in the future.) It does not require external power beyond a standard universal serial bus
(USB) port, and it is quite compact. Consequently, sensors in
this form factor have received significant attention from the
scientific community, particularly for environment mapping
and monitoring applications with UAVs [16], [17].
This article addresses the use of an off-the-shelf quadrotor
platform with a commercial off-the-shelf (COTS) RGB-D camera (see Figure 2). The current algorithms based on RGB-D
cameras need a large platform and specific customized hardware processors that are not widely available. These algorithms
generally only work without limitation on laptop or desktop
computers [18], [19]. Moreover, there is still a gap between the
use of complex algorithms in the research field and their use by
naive humans for everyday applications. Google's Project Tango
has bridged these gaps by creating a prototype [20] smartphone
IR Projector
RGB Camera
IR Camera

Figure 2. The Asus Xtion Pro live sensor.

June 2015

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IEEE ROBOTICS & AUTOMATION MAGAZINE

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http://www.diydrones.org
Table of Contents for the Digital Edition of IEEE Robotics & Automation Magazine - June 2015
