Coordinated USV Control
- Conference
- Location
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New Orleans, Louisiana
- Publication Date
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June 26, 2016
- Start Date
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June 26, 2016
- End Date
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June 29, 2016
- ISBN
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978-0-692-68565-5
- ISSN
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2153-5965
- Conference Session
- Tagged Division
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Ocean and Marine
- Page Count
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6
- DOI
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10.18260/p.26591
- Permanent URL
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https://peer.asee.org/26591
- Download Count
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267
Paper Authors
Lifford McLauchlan Texas A&M University, Kingsville
Dr. Lifford McLauchlan is an Associate Professor and Assistant Chair in the Electrical Engineering and Computer Science Department at Texas A&M University - Kingsville, and has also worked for Raytheon, Microvision, AT&T Bell Labs, and as an ONR Distinguished Summer Faculty at SPAWAR San Diego, CA. He has over 45 publications covering areas such as adaptive and intelligent controls, robotics, an ocean wave energy converter, green technology, education, wireless sensor networks and image processing. He is a co-inventor on 3 US patents related to control systems. Dr. McLauchlan is a member of ASEE and was previously the Chair of the Ocean and Marine Engineering Division and is now the Past Chair. He is also a member of IEEE (senior member), SPIE, Eta Kappa Nu, ACES and Tau Beta Pi, and has served on the IEEE Corpus Christi Section Board from 2004-2010 as Chair, Vice Chair, Secretary and Director. Dr. McLauchlan has received the Dean’s Distinguished Service Award twice and the Dean’s Outstanding Teaching Award once for the College of Engineering at Texas A&M University-Kingsville.
Mehrube Mehrubeoglu Texas A&M University, Corpus Christi
Dr. Mehrubeoglu received her B.S. degree in Electrical Engineering from The University of Texas at Austin. She earned an M.S. degree in Bioengineering and Ph.D. degree in Electrical Engineering from Texas A&M University. She is currently an associate professor in the School of Engineering and Computing Sciences at Texas A&M University-Corpus Christi. She is interested in multidisciplinary research in imaging applications using a variety of imaging modalities, including thermal imaging, hyperspectral imaging, and other digital imaging that engage targeted sensors, spatial and spectral data processing, pattern recognition and classification. She has a special interest in energy generation and real-world applications, as well as pedagogical methods in teaching and learning.
Abstract
Abstract
Many universities have lab exercises in the controls classes which consist of modeling and simulations for vehicles and robotics due to the costs associated with real vehicles, robotics or the test environments. Unmanned surface vehicles such as a Sea Fox can be modeled and simulated in Matlab or a similar software. Multiple vehicle paths can be coordinated to facilitate search patterns or to setup adhoc wireless sensor networks (WSNs) with the vehicles each possessing a node. At Texas A&M University-Kingsville an assignment for coordinated unmanned surface vehicle (USV) control and path planning has been developed. The work builds upon previous labs detailing the USV model and path planning using potential fields. The USVs are simulated in coordinated movements and in a coordinated search pattern. The system of USV systems is simulated in Matlab. This exercise introduces students to biomimetics and artificial intelligence methods such as models for flocking behavior or swarm intelligence. The group of vehicles’ coordinated paths and control can be augmented utilizing data from a WSN to ensure a more efficient path. The efficacy of the assignment is demonstrated through student engagement in the exercise.
McLauchlan, L., & Mehrubeoglu, M. (2016, June), Coordinated USV Control Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.26591
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