Short Bio

Dr. Erdal Kayacan received a Ph.D. degree in electrical and electronic engineering at Bogazici University, Istanbul, Turkey. After finishing his post-doctoral research at KU Leuven at the division of mechatronics, biostatistics and sensors (MeBioS) in 2014, he worked in Nanyang Technological University at the School of Mechanical and Aerospace Engineering as an assistant professor for four years. Currently, he is pursuing his research in Aarhus University at the Department of Engineering as an associate professor. He is the leader of Artificial Intelligence in Robotics (Air Lab) laboratory.

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“, Butterworth-Heinemann, Print Book ISBN:9780128026878. (17 Sept 2015).

He is a Senior Member of Institute of Electrical and Electronics Engineers (IEEE). From 1st Jan 2017, he is an Associate Editor of IEEE Transactions on Fuzzy Systems.

We are proud to announce our paper is accepted for publication in the 2019 International Conference on Robotics and Automation (ICRA) to be held on May 20-24, 2019 in Montreal, Canada.

Title: Online Deep Learning for Improved Trajectory Tracking of Unmanned Aerial Vehicles Using Expert Knowledge

Author: Andriy Sarabakha and Erdal Kayacan

For further details, see you at IEEE ICRA 2019 at Montreal!

Artificial Intelligence in Robotics Laboratory (Air Lab) is opened and open for research. Our new facilities in Skejby: Deep Tech Experimental Hub.

12 V8 Vicon cameras, 15x15x5 meters of flight arena!

New buildings in Singapore may soon have a high-tech building inspector rolling up to their door steps armed with laser scanners and high-tech cameras that can spot the tiniest cracks and defects.

This new building inspector is a robot invented by scientists from Nanyang Technological University, Singapore (NTU Singapore), co-developed with Singapore’s national industrial developer JTC and local start-up CtrlWorks.

Named QuicaBot – short for Quality Inspection and Assessment Robot – it can move autonomously to scan a room in minutes, using high-tech cameras and laser scanners to pick up building defects like cracks and uneven surfaces.

A few of these robots working together will make inspecting a building a breeze. The robots can upload 3D data of the scans to the cloud and inform the human operator, who can then inspect critical and complex defects.

“Visual inspection of a new building is an intensive effort that takes two inspectors, so we have designed a robot to assist a human inspector to do his job in about half the time, saving precious time and manpower, and with great accuracy and consistency,” explained Prof Kayacan.

Reuters: http://www.reuters.com/video/2016/09/26/scientists-create-building-inspection-ro?videoId=369951376

Fuzzy Neural Networks for Real Time Control Applications: Concepts, Modeling and Algorithms for Fast Learning
by Erdal Kayacan and Mojtaba Ahmadieh Khanesar
With foreword by Jerry M. Mendel

AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS

Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book!

Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book.

Google Scholar: http://scholar.google.com.sg/citations?user=50TLpi4AAAAJ&hl=en

ISI ResearcherID: http://www.researcherid.com/rid/D-6256-2014

ResearchGate: http://www.researchgate.net/profile/Erdal_Kayacan

Twitter: https://twitter.com/AUAirLab