LABUST has taken part in many scientific research projects relating to underwater systems and technologies in various roles. This includes numerous international (FP7, H2020, ONRG, INTERREG,...) as well as national projects.
As part of the UWIN-LABUST project, the Laboratory for Underwater Systems and Technologies in collaboration with the IEEE Croatia Section - Robotics and Automation Chapter, the IEEE OES University of Zagreb Student Branch Chapter and IEEE Life Member Affinity Group - Croatia is happy to invite you to the lecture
"Research activities at the Visual Cognitive Systems Laboratory at the University of Ljubljana, Faculty of Computer and Information Science"
held by Engr. Matej Dobrevski - Ph.D. student at the Visual Cognitive Systems Laboratory at the University of Ljubljana, Faculty of Computer and Information Science. The lecture will take place on Friday, October 20th, 2023 at 13:00 in the Grey Hall of the Faculty of Electrical Engineering and Computing (FER). The lecture is in English.
The lecturer’s CV and the summary of the lecture can be found below.
As mobile robots continue to play an increasingly vital role in diverse applications, ensuring their safe and efficient navigation in unstructured environments remains a paramount challenge. The navigation problem can be effectively decomposed into distinct components: perception, localization, planning, and control. However, the multitude of algorithms and approaches available for each of these tasks underscores the complexity of the challenge, with no one-size-fits-all solution. In recent years, the remarkable capabilities of deep neural networks in function modeling have opened up many possibilities for addressing these challenges. In the context of robotics, Deep Reinforcement Learning (DRL) is especially promising, since it enables the training of neural networks through interaction with the environment, without the need for labeled samples. Leveraging model-free DRL, our research has focused on harnessing the power of neural networks for mobile robotics. I will present our work in applying DRL to train neural networks for navigation of mobile robots. I will talk about the practical and theoretical considerations essential for the implementation of DRL in the field of robotics.
Matej Dobrevski is a control engineer, turned roboticist, turned PhD student at the Visual Cognitive Systems Laboratory at the University of Ljubljana, Faculty of Computer and Information Science under the supervision of Prof. Danijel Skočaj. His interests are deep learning computer vision and robotics. He has worked on various projects in computer vision.