Semi-Autonomous
Vehicle Intelligence |
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Unmanned Ground Vehicles (UGVs) have advantages
over people in a number of different
applications, ranging from sentry duty, scouting
hazardous areas, convoying goods and supplies
over long distances, and exploring caves and
tunnels. Despite recent advances in
electronics, vision, artificial intelligence,
and control technologies, fully autonomous UGVs
are still far from being a reality. Currently,
most UGVs are fielded using tele-operation with
a human in the control loop. Using
tele-operations, a user controls the UGV from
the relative safety and comfort of a control
station and sends commands to the UGV
remotely. It is difficult for the user to
issue higher level commands such as patrol this
corridor or move to this position while avoiding
obstacles. As computer vision algorithms
are implemented in hardware, the UGV can easily
become partially autonomous. As Field
Programmable Gate Arrays (FPGAs) become larger
and more powerful, vision algorithms can run at
frame rate. With the rapid development of
CMOS imagers for consumer electronics, frame
rate can reach as high as 200 frames per second
with a small size of the region of
interest. This increase in the speed of
vision algorithm processing allows the UGVs to
become more autonomous, as they are able to
recognize and avoid obstacles in their path,
track targets, or move to a recognized
area. The user is able to focus on giving
broad supervisory commands and goals to the
UGVs, allowing the user to control multiple UGVs
at once while still maintaining the convenience
of working from a central base station. In
this research, we will describe a novel control
system for the control of semi-autonomous
UGVs. This control system combines a user
interface similar to a simple tele-operation
station along with a control package, including
the FPGA and multiple cameras. The control
package interfaces with the UGV and provides the
necessary control to guide the UGV.
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Graduate Students:
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Jonathan Anderson, Beau Tippetts, and Zhaoyi
Wei
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Publications:
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B.J. Tippetts, D.J. Lee, and J.K
Archibald, “An On-Board Vision Sensor
System for Small Unmanned Vehicle Applications,”
Machine Vision and Applications Journal, vol.
23/3, P.405-413, May, 2012.
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J.D.
Anderson, D.J. Lee, R.B Schoenberger,
and B.J. Tippetts, “Using Real-time
Vision to Control a Convoy of
Semi-Autonomous Unmanned Vehicle”, AUVSI’s
Unmanned Systems North America, online
proceedings, Orlando, Florida, August 29-31,
2006.
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J.D. Anderson, D.J. Lee, Z. Wei,
and J.K. Archibald, “Semi-Autonomous
Unmanned Ground Vehicle Control System”, SPIE
International Symposium on Defense and
Security, Unmanned Systems Technology VIII,
vol. 6230-66, 62301M, Orlando, Florida, USA,
April 17-21, 2006.
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