IEEE SMC Beijing Capital Region Chapter Seminar by Professor Erdal Kayacan of Aarhus University
On the afternoon of May 21, at the invitation of Professor Zhijie Liu, Professor Erdal Kayacan, gave an academic presentation entitled "Future of Smaller Faster More Agile, Yet Safer Aerial Robots: Challenges & Opportunities" through Skype. The lecture was hosted by Zhijie Liu. faculty members and more than 50 doctoral and master's degree students attended the lecture.
During the presentation, Professor Erdal Kayacan shared his experience in Future of Smaller Faster More Agile, Yet Safer Aerial Robots. First, Professor Erdal Kayacan introduced both model-based and model-free learning methods to handle various real-time aerial robot control problems. Then, Professor Erdal Kayacan introduced deep learning methods for perception and planning of aerial robots as applied to the autonomous drone racing problem. Finally, Professor Erdal Kayacan addressed the anomaly detection problem using drones. A deep neural network-based method will be introduced to find point anomalies (i.e., single instance anomalous data) and contextual anomalies (i.e., context-specific abnormality) in an environment using a UAV.
During the question-and-answer session, the teachers and students of the School of Automation actively asked questions, and Professor Erdal Kayacan answered them one by one. In this report meeting, Professor Erdal Kayacan and Automation College teachers and students have a cordial academic exchanges, enriched the knowledge of students, broaden their horizons in academic and scientific research.
Brief introduction of the presenter:
Erdal Kayacan received a Ph.D. degree in electrical and electronic engineering at Bogazici University, Istanbul, Turkey in 2011. After finishing his post-doctoral research in University of Leuven (KU Leuven) in 2014, he worked in Nanyang Technological University (NTU), Singapore at the School of Mechanical and Aerospace Engineering as an assistant professor for four years. Currently, he is pursuing his research at Aarhus University at the Department of Electrical and Computer Engineering as an associate professor and he is the Director of Artificial Intelligence in Robotics Laboratory (AiR Lab).
He has since published more than 140 peer-refereed book chapters, journal and conference papers in model-based and model-free control, parameter and state estimation, computer vision, motion and path planning for robots. He has completed a number of research projects which have focused on the design and development of ground and aerial robotic systems, vision-based control techniques and artificial intelligence. He is currently involved in a number EU projects; some of which are “Reliable AI for Marine Robotics” by Horizon 2020 - H2020-MSCA-ITN-2020, European Union and “Open Deep Learning toolkit for Robotics” by Robotics Core Technology ICT-10-2019-2020, European Union. Dr. Kayacan is co-writer of a course book “Fuzzy Neural Networks for Real Time Control Applications, 1st Edition Concepts, Modeling and Algorithms for Fast Learning”. He is a Senior Member of Institute of Electrical and Electronics Engineers (IEEE) and members of Computational Intelligence Society and Robotics and Automation Society. Since 1st Jan 2017, he is an Associate Editor of IEEE Transactions on Fuzzy Systems (TFS) and IEEE/ASME Transactions on Mechatronics (TMECH). He is also the manager of Junior Reviewer Program in TMECH, which is intended to introduce young researchers in the mechatronics research community to the best practices in peer-reviewing of scientific publications under the guidance of Editorial Board members.
