Atlanta, Georgia
June 23, 2013
June 23, 2013
June 26, 2013
2153-5965
Ocean and Marine
10
23.983.1 - 23.983.10
10.18260/1-2--22368
https://peer.asee.org/22368
397
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.
Problem Based Learning Through Modeling and Simulation of Unmanned VehiclesProblem based learning has been shown to increase student excitement and attention which will increasestudent understanding of course material and concepts. With the high cost of large scale underwater,land and air vehicles, the use of modeling and simulation capabilities becomes more important foruniversity programs. Autonomous Unmanned Vehicle (AUV) Workbench was developed as a modelingand simulation environment to enable physics based real time simulation of autonomous vehicles, suchas surface, underwater, land and air. Vehicle missions can also be replayed for further study. Labexercises have been created for the students to illustrate waypoint navigation and control for underwatervehicles. By enabling the student to see the effects of the control algorithm in the simulated actions,Freshman students gain a larger scale understanding of more advanced concepts that they will learn thetheory for during their junior and senior years; thereby allowing the students to gain insights into how thetheory in various undergraduate classes may be used in applications. AUV Workbench simulationenvironment enhances the student’s understanding of modeling systems.
McLauchlan, L., & Mehrubeoglu, M., & Durham, J. (2013, June), Problem Based Learning Through Modeling and Simulation of Unmanned Vehicles Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--22368
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