- Associate Professor of Mechanical Engineering and Program Coordinator for the Ph.D. in Mechanical Engineering
- Eric.Coyle@erau.edu Email
- Mechanical Engineering Department
- Daytona College of Engineering
Eric J. Coyle is an Associate Professor of Mechanical Engineering at Embry-Riddle Aeronautical University and has been at the University since 2011. He received his Ph.D. in Mechanical Engineering from Florida State University in 2010 and where he was part of the Center for Intelligent Systems, Control and Robotics. Dr. Coyle teaches courses in robotics, controls, signal processing, and machine learning. He also serves as an adviser for the Robotics Association at Embry-Riddle Aeronautical University which participates in multiple collegiate robotics competitions. His research focuses on perception, machine learning, control, and guidance of autonomous vehicles. His current research projects include the design of maritime perception systems and autonomous vehicle path planning.
- Ph.D. - Doctor of Philosophy in Mechanical Engineering, Florida State University
- ME 311: Robotic Tchnlgs Unmanned Systm
ME311 Robotics Technologies for Unmanned Systems
ME402 Robotic Arms
ME407 Preliminary Design of Robotic Systems with Laboratory
ME437 Senior Design of Robotic Systems with Laboratory
ME520 Sensor Processing with Applications
ME527 Modern Control Systems
ME540 Engineering Practicum
ME595C Software Implementation Design Projects
ME595V LabVIEW for Robotic and Mechatronic Systems
ME615 Pattern Recognition and Machine Learning
C. Hockley, T. Zuercher, H. Patel, C. Kennedy, E. Coyle, P. Currier, B. Butka, and C. Reinholtz, Results from the ERAU Maritime RobotX Entry, Association for Unmanned Vehicle Systems International Unmanned Systems, Atlanta, GA, 2015.
J. Shill, E. G. Collins, E. Coyle, and J. Clark, Tactile surface classification for limbed robots using a pressure sensitive robot skin. Bioinspiration & Biomimetics, 10(1), 2015.
C. Hockley, T. Zuercher, E. Coyle, and P. Currier, System Architecture, Development and Results of the Embry-Riddle Aeronautical University Maritime RobotX Platform, American Institute of Aeronautics and Astronautics InfoTech@Aerospace Conference, Kissimmee, FL, 2014.
C. Hockley, T. Zuercher, H. Patel, G. Gamble, C. Kennedy, E. Coyle, P. Currier, and C. Reinholtz, The Development of the ERAU Maritime RobotX Challenge Autonomous System, Association for Unmanned Vehicle Systems International Unmanned Systems, Orlando, FL 2014.
W. Barott, E. Coyle, T. Dabrowski, C. Hockley, and R. Stansbury. Passive Multispectral Sensor Architecture for Radar-EOIR Sensor Fusion for Low SWAP UAS Sense and Avoid. IEEE/ Position Location and Navigation Symposium, Monterrey, CA, 2014.
R. S. Stansbury, J. Olds, E. Coyle, “Ethical Concerns of Unmanned and Autonomous Systems in Engineering Programs,” American Society of Engineering and Education Symposium, Indianapolis, IN, 2014.
E. Coyle, R. G. Roberts, E. G. Collins, A. Barbu. Synthetic data generation for classification via uni-modal cluster interpolation. Autonomous Robots, DOI 10.1007/s10514-013-9373-9, 2013.
L. Lu, C. Ordonez, E. G. Collins, Jr., E. Coyle, and D. Palejiya. Terrain surface classification with control mode update rule using 2D laser stripe-based structured light sensor. Robotics and Autonomous Systems, 59(11):954-965, 2011.
E. Coyle, E. G. Collins, Jr., and R. G. Roberts. Speed independent terrain classification using singular value decomposition interpolation. International Conference on Robotics and Automation, Shanghai, China, 2011.
H. Wang, E. Coyle, C. Chung, W. Bates, D. Ding, E. Collins, and R. A. Cooper. How Driving Parameters Affect an Electrical Powered Wheelchair's Slip on Different Terrains. Proceedings of the Rehabilitation Engineering and Assistive Technology Society of North America Conference, Toronto, ON, Canada, 2011.
E. Coyle, E. G. Collins, Jr., and L. Lu. Updating control modes based on terrain classification. In International Conference on Robotics and Automation, Anchorage, Alaska, 2010.
E. G. Collins, Jr. and E. Coyle. Vibration-based terrain classification using surface profile input frequency responses International Conference on Robotics and Automation, Pasadena, California, 2008.
E. M. DuPont, E. G. Collins, Jr., E. Coyle, and R. G. Roberts. Terrain classification using vibration sensors: theory and methods. In New Research on Mobile Robotics. NOVA, 2008.