IEEE Systems, Man and Cybernetics Magazine - October 2019 - 31

Army Research Office, Aberdeen Proving Ground, Maryland, and commander of the U.S. Army Yuma Proving
Ground, Arizona. He is a member of the American Society
of Mechanical Engineers, the Association for Unmanned
Vehicle Systems International, and the National Defense
Industrial Association.
Kyle Snyder (kyle.snyder@cn-bus.com) earned his B.A.
degree in mathematics and computer science from Catawba
College, Salisbury, North Carolina, his M.S. degree in
applied mathematics at the University of Tennessee Space
Institute in Tullahoma, and his M.B.A. degree in aerospace
from the University of Tennessee in Knoxville, in 1996, 1998,
and 2005, respectively. He is currently employed by Cherokee Nation Strategic Programs as the Department of Homeland Security Robotics Integration program manager in
Arlington, Virginia. Previously, he launched the Unmanned
Aircraft Systems (UAS) programs at North Carolina State
University (NCSU) in Raleigh and Middle Tennessee State
University in Murfreesboro. He has more than 20 years of
experience in researching, developing, testing, educating,
and integrating advanced aviation and unmanned systems
technologies. He is a member of the Association for
Unmanned Vehicles Systems International. He is a recognized speaker and subject matter expert often invited to
present on how drones continue to personalize aviation as
never before and how the interfaces between people and
robots are becoming ever more frequent opening many new
opportunities for expanding human performance.
Raymond Scott Swanson (raymond.s.swanson@
lmco.com) earned his B.S.E.E. degree from California
State University, Fresno, in 1985. He worked for Lockheed
Martin Aeronautics, Fort Worth, Texas, for 15 years and
also led several critical initiatives for Lockheed Martin
Corporation, including duties as a primary radar technical
team member and subject matter expert for the F-16/
Block 60 radar team. Prior to joining Lockheed Martin, he
served in a variety of increasingly responsible positions at
various other Department of Defense/U.S. government
agencies for 18 years, including Raytheon-Texas Instruments Systems, Alliant Tech Systems, Sierra Nevada Corporation, and the Naval Air Warfare Center, where he
served both as a senior electronics engineer and a senior
systems engineer for a variety of U.S. Navy- and Air
Force-related projects/efforts. He is a senior member of
the American Institute of Aeronautics and Astronautics
and technical committee member for the Sensor Systems
and Information Fusion focus area. In addition, he is a
member of the Association of Old Crows.
Mo Jamshidi (Mo.Jamshidi@utsa.edu) earned his B.S.
degree in electrical engineering from Oregon State University, Corvallis, in 1967, and his M.S. and Ph.D. degrees in electrical engineering from the University of Illinois at Urbana-
Champaign, in 1969 and 1971, respectively. He holds an honorary doctorate degree from the University of Waterloo,
Canada (2004); the Technical University of Crete, Greece
(2004), and Odlar Yourdu University, Baku, Azerbaijan

(1999). He is the Lutcher Brown Endowed Chair and Distinguished Professor at the University of Texas, San Antonio,
and has been an advisor for more than 70 M.S. degree and
65 Ph.D. degree students. He received the IEEE Centennial
Medal, IEEE Millennium Award, and IEEE Norbert Weiner
Research Achievement Award, and the 2014 IEEE-USA Systems Engineering Career Award, among others. He is a Life
Fellow of the IEEE.
Younho Seong (yseong@ncat.edu) earned his B.S. and
M.S. degrees in industrial engineering from Inha University,
Incheon, South Korea, in 1991 and 1993, respectively, and
his Ph.D. degree in industrial engineering from the State
University of New York at Buffalo, in 2002. He is an associate professor of industrial and systems engineering at North
Carolina A&T State University (NCA&TSU), Greensboro. He
is with the Testing, Evaluation, and Control of Heterogeneous Large-Scale Systems of Autonomous Vehicles Center
at NCA&TSU.
Emily A. Doucette (emily.doucette@us.af.mil) earned
her Ph.D. degree in aerospace engineering from Auburn
University, Alabama, and is a recipient of the Science,
Mathematics and Research for Transformation Scholarship. She serves as multidomain networked weapons
technical lead for the Air Force Research Laboratory
Munitions Directorate, Eglin Air Force Base, Florida.
Prior to this post, she served the Munitions Directorate as
the assistant to the chief scientist from 2017 to 2019 and
as a research engineer for the Weapon Dynamics and Control Sciences Branch since 2012. She served on the Air
Force Research Laboratory Munitions Directorate Autonomy Steering Committee, is active in the Autonomy Community of Interest, and is the co-lead for the Office of the
Secretary of Defense Autonomy Center of Excellence.
References
[1] D. Levi, N. Garnett, and E. Fetaya, "Stixelnet: A deep convolutional network for
obstacle detection and road segmentation," in Proc. British Machine Vision Conf.
(BMVC), 2015, pp. 109.1-109.12. doi: 10.5244/C.29.109.
[2] M. Kristan, V. Sulic´ Kenk, S. Kovacˇicˇ, and J. Perš, "Fast image-based obstacle
detection from unmanned surface vehicles," IEEE Trans. Cybern., vol. 46, no. 3,
pp. 641-654, Mar. 2016. doi: 10.1109/TCYB.2015.2412251.
[3] K.-H. Chao and P.-Y. Chen, "An intelligent traffic flow control system based on radio
frequency identification and wireless sensor networks," Int. J. Distrib. Sens. Netw., vol.
10, no. 5, pp. 54-69, 2014. doi: 10.1155/2014/694545.
[4] M. Luck, M. D'Inverno, and S. Munroe, "Autonomy: Variable and generative," in
Agent Autonomy, H. Hexmoor, C. Castelfranchi, and R. Falcone, Eds. Boston: Springer,
2003, pp. 11-28.
[5] R. C. Arkin and R. R. Murphy, "Autonomous navigation in a manufacturing
environment," IEEE Trans. Robot. Autom., vol. 6, no. 4, pp. 445-454, Aug. 1990. doi:
10.1109/70.59355.
[6] S. Shen, N. Michael, and V. Kumar, "Autonomous multi-floor indoor navigation with
a computationally constrained MAV," in Proc. Int. Conf. Robotics Automation (ICRA),
2011, pp. 20-25.
[7] D. A. Pomerleau, "Efficient training of artificial neural networks for autonomous navigation," Neural Comput., vol. 3, no. 1, pp. 88-97, 1991. doi: 10.1162/
neco.1991.3.1.88.

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IEEE Systems, Man and Cybernetics Magazine - October 2019

Table of Contents for the Digital Edition of IEEE Systems, Man and Cybernetics Magazine - October 2019

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