My main research interests and contributions lie within the areas of control systems, artificial intelligence, mechatronics, robotics, guidance, control and automation of unmanned ground and aerial vehicles. The main motivation of my research has always been to inject “learning” phenomena into various types of control algorithms as well as their real time implementations.
My contributions to interval type-2 fuzzy neural networks have made a notable impact on the computational intelligence community and have also received significant international recognition. The outcomes and findings of my research have been regularly peer reviewed and accepted for the best journals in the relevant field – IEEE Transactions and premier international conferences, such as Fuzzy Systems (FUZZ-IEEE).
I am the first author of a course book “Fuzzy Neural Networks for Real Time Control Applications, 1st Edition Concepts, Modeling and Algorithms for Fast Learning”, published by Elsevier. Among the other books in type-2 fuzzy logic theory, I believe that this book has the most comprehensive stability analysis for type-2 fuzzy logic systems.
During my post-doctoral research at the University of Leuven (KU Leuven), my field of expertise was the real time implementation of unmanned ground robots. I focused on system modeling, identification and control of large scale systems, complex mechatronic systems and robotics guidance. Within the framework of agricultural robotics, my group and I designed a fully autonomous tractor-implement system, and equipped it with various sensors and actuators. The outcome of this project was a practical mechatronic system, illustrating how control, sensing, and actuation can be integrated to achieve an intelligent system.
I am currently investigating guidance and vision-based control of unmanned aerial robots. Visual tracking is a critical task in numerous applications and has attracted a lot of attention in the computer vision community. However, an ideal tracker that outperforms others in all situations does not exist due to the difficulties of recognizing a target undergoing occlusion, rotation, appearance variations or illumination changes. Currently, I have two ongoing industrial research projects. The first focuses on the guidance of unmanned aerial robots by using novel tracking algorithms. The second project aims to implement learning control strategies on unmanned aerial vehicles to improve their control accuracy as well as their capabilities to function under uncertain working environments.
Not only drones but also all different applications of robots are going to be one of the most significant technologies for the next few decades. Therefore, in the future, I hope to focus on unmanned ground and aerial vehicles and their daily life applications by enriching their capabilities using vision-based algorithms. The future of drones is very promising and will be an area of ongoing development. Therefore, my long term research agenda includes creating a link between control theory (in particular learning control strategies), artificial intelligence, robotics and vision.
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