Dr. Hakki Erhan Sevil

  • Position:  Assistant Professor
  • Department:  Intelligent Systems and Robotics
  • Office Location:  Campus: Building 4, Room 139; Downtown: 220 W Garden St, Suite 250, Office 224
  • Campus: 850.474.3236
  • Google Scholar


Dr. Hakki Erhan Sevil received his Doctor of Philosophy degree in Mechanical Engineering from the University of Texas at Arlington (UTA) in 2013, and his Bachelor of Science and Master of Science degrees in Mechanical Engineering from Izmir Institute of Technology, Turkey, in 2004 and 2006, respectively. He had over 4 years of research experience at Izmir Institute of Technology, and he was a Visiting Researcher in Service Automation and Systems Analysis (Service d'Automatique et d'Analyse des Systemes - SAAS) Laboratory at Universite Libre de Bruxelles (ULB) in 2009. Between 2009 and 2013, he was conducting research in Computer Aided Control System Design Laboratory (CACSDL) and Autonomous Vehicles Laboratory (AVL) at UTA.

Before joining University of West Florida (UWF) in 2018, he has worked as a Research Scientist at the University of Texas at Arlington Research Institute (UTARI) between 2014 and 2018. His research interests include robotics, guidance and path planning, fault detection and isolation, autonomous navigation and obstacle avoidance. Dr. Sevil has authored/coauthored more than 35 journal and conference papers, one book chapter, and he has been involved in 10 funded projects as a researcher. One of these projects, titled “Variable Autonomy of small UAVs (Unmanned Aerial Vehicles) for NAS (National Airspace System) Integration”, was funded by the National Aeronautics and Space Administration (NASA) and the National Institute of Aerospace (NIA).

Besides working on the funded projects as a key personnel, Dr. Sevil also has been a Co-PI for a sponsored research project funded by VectorNav, LLC. More recently, Dr. Sevil has been a Co-PI on the “Adaptive Robotic Nursing Assistants (ARNA)” project funded by National Science Foundation (NSF). Additionally, he has been the Principal Investigator (PI) of various internal projects at UTARI. His recent work includes resilient and intelligent robotic systems, cooperative unmanned vehicles, object detection and tracking using computer vision methods, and advanced guidance and navigation techniques.

Degrees & Institutions:

Ph.D. Mechanical Engineering, the University of Texas at Arlington
M.S. Mechanical Engineering, Izmir Institute of Technology
B.S. Mechanical Engineering, Izmir Institute of Technology


Dr. Sevil is interested in studying problems of theoretical and practical effects, and he is eager to examine real world implementations in different domains while aiming to plan techniques that offer solutions to a wide spectrum. His methodological and theoretical research as well as a considerable portion of his applied and collaborative work focuses on fault detection and isolation (FDI) of dynamical systems, condition monitoring, autonomous navigation, obstacle avoidance, and implementation of computational methods. Dr. Sevil is currently working towards further exploring implementation of intelligence systems on a wider spectrum of real world applications especially in fully autonomous, unmanned, self-sustained, resilient and smart systems. All of his methodological and theoretical work is extendable to different engineering practices. His current research primarily focuses on advanced guidance, navigation, and control systems, as well as fault tolerant systems for unmanned vehicles. Dr. Sevil is also interested in developing more sophisticated, advanced and complex systems as a result of the combination of his previous research work.

Current Courses:

  • EML 4804 Mechatronic Systems
  • EML 4804L Mechatronic Systems Lab

Special Interests:

Machine Learning, Reinforcement Learning, Bio-inspired robotics, Swarm intelligence, Dynamic Systems Modeling and Control

Keywords: Robotics, fault detection and isolation (FDI), autonomous navigation, obstacle avoidance, intelligence systems, unmanned vehicles, object detection and tracking.