Indianapolis, Indiana
June 15, 2014
June 15, 2014
June 18, 2014
2153-5965
Ocean and Marine
10
24.59.1 - 24.59.10
10.18260/1-2--19951
https://peer.asee.org/19951
392
Dr. Lifford McLauchlan completed his Ph.D. at Texas A&M University, College Station. After spending time in industry, he has returned to academia. He is an associate professor at Texas A&M University -Kingsville in the Electrical Engineering and Computer Science Department. His main research interests include controls, robotics, education, adaptive systems, intelligent systems, signal and image processing, biometrics and watermarking. He is the current chair of the ASEE Ocean and Marine Engineering Division and is a senior member of IEEE.
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.
A Laboratory Exercise - Unmanned Vehicle Control and Wireless Sensor NetworksAbstractWith the ever decreasing cost of processors and electronics in general, wireless sensor networks(WSNs) are increasingly being utilized for environmental measurements. Different WSNtopologies will allow different sensor coverages and energy utilizations for a given application.These WSNs can then be utilized as “extra eyes and ears” for an unmanned vehicle traversing theenvironment. A vehicle’s path and control can be improved by using the WSN more efficientlyto ensure proper vehicle operation in the given application.At a new lab exercise for an unmanned vehicle such as an underwatervehicle or surface vehicle has been created for students to demonstrate how the sensor networkimproves the vehicle’s control and path planning. Simple sensor models are developed in theexercise. The physics based model is analyzed for the vehicle. The lab exercise next develops thecontrol of the vehicle system which uses “simulated sensor” inputs from the WSN and has thestudent analyze the corresponding closed loop control system utilizing the “simulated sensornetwork” inputs. The closed loop system is simulated utilizing Matlab. The lab demonstrates tostudents the increased utilization of WSNs for use in various applications such as controlsystems.
McLauchlan, L., & Mehrubeoglu, M. (2014, June), A Laboratory Exercise - Unmanned Vehicle Control and Wireless Sensor Networks Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--19951
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