Gantry Helps Test Unmanned Aerial Vehicles
in Near-Earth Environment
realm of unmanned aerial vehicles (UAVs) is expanding, moving down from
high altitudes and clear skies to fly amongst buildings and in forests.
Flying close to the earth presents many challenges, from cluttered
terrain to adverse weather conditions such as fog, rain, or dust. The
UAV must be outfitted with sensors to map the environment and control
algorithms to navigate it from point to point while compensating for
wind gusts and dodging obstacles. The Drexel Autonomous Systems Lab
(DASL) has set out to solve these problems.
DASL is a robotics lab located on the campus of Drexel University in the
center of Philadelphia, Pennsylvania. The lab is run by Paul Oh,
professor of Mechanical Engineering and director of Robotics for the
National Science Foundation. DASL is the largest robotics lab on
Drexel’s campus, and develops many different autonomous systems, from
autonomous all-terrain vehicles to walking humanoid robots. It is well
known for its work on UAVs, specifically on the sensing and control
algorithms for flying UAVs in near-earth environments.
logged many hours flying autonomous planes and helicopters, the
researchers noted that field tests come at a high cost in terms of both
time and money. “The preparation for a field test and waiting for good
weather to fly can take up to two weeks,” said Keith Sevcik, a
researcher at DASL. “We live in fear of crashes. A crash can set you
back thousands of dollars and months of development time. Most of our
time is spent testing systems and building in safety measures to avoid
crashes. The actual flights only last a couple of hours at most.”
Flight tests are the cornerstone of UAV research. The tests ensure that
hardware and software systems work in concert, bridging the gap between
lab development and real world application. But the cost of performing
flights drives most researchers to focus on computer simulations,
leaving the issues of implementation to someone else. There was no
existing method to test computer code, flight control systems, sensors
and other hardware without actually flying the UAV. To address this
issue, the researchers at DASL envisioned the Systems Integrated Sensor
Test Rig (SISTR).
is a hardware-in-the-loop test rig that can be used to characterize and
design sensor suites, test control algorithms and emulate flight tests.
The facility is designed to virtually fly the UAV sensors through a
realistic environment. Sensor data feeds into a high-fidelity math model
of the aircraft, which generates the aerial robot’s motion with a six-dof
gantry. This allows the UAV to be rapidly developed in a controlled,
The heart of the rig is a three-degree of freedom gantry from Techno,
Inc., New Hyde Park, New York, that was custom built to provide the
speeds and accelerations needed to simulate UAV flight. “The gantry has
to have a large envelope of approximately 15 feet wide by 20 feet long
by 10 feet high to enable the UAV to fly completely through the
environment,” Sevcik said. “In addition, it needs very fine motion
control and high levels of speed and acceleration to simulate UAVs
flying through the space. Techno, Inc. provided a gantry table that
meets all of these requirements.”
gantry’s brushless DC motors position the gantry arm. The maximum
payload is 35 pounds. The gantry has an x-axis travel of 17.72 feet,
x-axis speed of 2 feet per second and x-axis acceleration of 2.95 feet
per second squared. It has an y-axis travel of 13.84 feet, y-axis speed
of 2 feet per second and y-axis acceleration of 3.69 feet per second
squared. The gantry has a z-axis travel of 5.43 feet, z-axis speed of 2
feet per second and z-axis acceleration of 7.40 feet per second squared.
The remaining three degrees of freedom are provided by a Drexel-made
pan/tilt/roll unit attached to the end of the gantry beam. The axes of
rotation intersect at the center of the sensor, mimicking how most
aircraft rotate at their center. This approach decouples rotations,
allowing independent control over each axis. The pan/tilt/roll unit was
constructed from Dynamixel AX-12 servos because of their small size,
high torque, high speed and resolution.
environment is represented by a scaled mockup of a near-earth
environment. By scaling down the environment, a much larger area can be
recreated inside the confined lab space. The environment was created at
1/87 scale so that HO railroad accessories can be used to dress up the
model. The buildings and other manmade structures were created from foam
core board. Natural features were roughly approximated using modeling
A non-flying mockup of the UAV equipped with collision-avoidance sensors
is attached to the gantry. The sensor data feeds into a high-fidelity
math model of the real-world aircraft. The math model is used to control
the motion of the gantry. The test rig also has a rain machine, dust
machine, fog system, fans and lamps to reproduce rain, dust and fog.
Twelve 750 watt lamps on the top of the rig are used to simulate day and
night conditions. The environmental conditions in the facility can be
adjusted in a controlled, repeatable manner.
The gantry is able to duplicate a large portion of the operating range
of the UAV. All translational axes can be controlled within +/-0.5 cm.
This scales up to a resolution of +/-0.43m, well within the +/-2m
accuracy of off-the-shelf GPS systems. Sensors are mounted on the gantry
and virtually flown through the environment. Real-time data is collected
by the same software that will be used in flight. Control commands are
fed into a mathematical model of the aircraft, which generates aircraft
positions that are used to drive the gantry.
Evaluating UAV performance on test rig
aircraft control software simulates the motion of the aircraft at full
scale. The resulting position of the aircraft is then scaled and used to
command the gantry. The test rig was used to investigate how the
aircraft dynamics are affected by scaling. “Performance is greatly
affected by the update rate,” Sevcik said. “The faster the communication
between the software and the gantry, the more accurately that motion can
be controlled. This directly affects the range of speeds that can be
accurately reproduced. Faster speeds demand more position commands per
Aircraft were flown in the test rig at unscaled speeds ranging from 1
meter per second to 40 meters per second. The velocity was gradually
varied to determine if there is an upper or lower bound on the
boundaries that the test rig could reproduce. When the aircraft was
moving at velocities greater than 30 meters per second the motion was
erratic because the control was not updating fast enough. When the
aircraft was moving slowly at around one meter per second, it was
difficult to overcome static friction. Acceptable results were seen in
the range between these extremes and the best results were obtained in
the neighborhood of five meters per second.
scaled tests were verified against baseline computer simulations. A
standard UAV mission was selected in which the UAV uses a camera to
guide itself to the center of a window while remaining a fixed distance
from the building. Results showed that the tests at 1/87 scale were
similar to simulations. After the scaled tests were validated,
experiments were conducted to see how illumination and obscurants affect
illumination decreases, features around the windows of the building are
lost,” Sevcik. “Instead, the white border around the top of the building
is favored. Also, a shadow on the top of the building becomes more
prominent as the lighting decreases, causing a feature to be detected on
the roof. Generally, decreased illumination results in weaker and more
difficult to track features. After testing the effect of lighting, fog
was introduced. Fog tends to wash out the image but the same features
are detected. However, these features are not as strong and more
difficult to track. Though fog and weak illumination results in weaker
features, vision still worked under these conditions.”
The test rig can be quickly outfitted with different aircraft models,
control algorithms and sensors,” Sevcik concluded. “The Techno, Inc.
gantry delivers the speed, acceleration and accuracy needed to simulate
UAV flight. The environmental conditions in the rig can be adjusted in a
controlled, repeatable manner. These results show scaling to be a
promising avenue for designing UAV sensors, algorithms and missions. In
particular it shows promise for developing algorithms that work under
-- gantry: The Techno gantry is the heart of Drexel’s Systems Integrated
Sensor Test Rig (SISTR). SISTR is a realistic testing environment for
UAVs with the ability to recreate different environments and weather
-- scaledModelVisionTests036: DASL is investigating the feasibility of
testing UAV sensing and control algorithms in scaled down environments.
-- gantry_blackhawk: The Drexel made Blackhawk MAV undergoing testing on
the gantry. Blackhawk’s sensor package is affixed to the gantry, and the
gantry mimics the motion of the aircraft.
-- IMG_0048 and IMG__0050: The Drexel made Blackhawk MAV undergoing
testing on the gantry. Blackhawk’s sensor package is affixed to the
gantry, and the gantry mimics the motion of the aircraft.
-- scaledTests_072009071: As the UAVs are virtually flown through the
environment, real-time data is collected by the same software that will
be used in flight.
--scaledModelVisionTests054: The UAV’s sensor suite is affixed to a
pan/tilt/roll unit at the end of the gantry, allowing it to be “flown”
through the mock environment.
--gantryWithAirscout: The Techno gantry is capable of lifting 35 lbs,
allowing full scale UAVs to be attached to the end effector for
collision avoidance tests.
For more information on the gantry described in this article, contact:
Techno, Inc. Linear Motion Systems, 2101 Jericho Turnpike, New Hyde
Park, NY 11040. Phone: 516-328-3970 Fax: 516-358-2576 E-mail:
LINEAR MOTION SYSTEMS
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