Projects

The Industry 4.0 National Technology Platform was established under the leadership of the Institute for Computer Science and Control (SZTAKI), Hungarian Academy of Sciences, with the participation of research institutions, companies, universities and professional organizations having premises in Hungary, and with the full support and commitment of the Government of Hungary, and specifically that of the Ministry of National Economy.

The aim of the present study is to develop and evaluate a computer-based methods for automated and improved detection and classification of different colorectal lesions, especially polyps. For this purpose first, pit pattern and vascularization features of up to 1000 polyps with a size of 10 mm or smaller will be detected and stored in our web based picture database made by a zoom BLI colonoscopy. These polyps are going to be imaged and subsequently removed for histological analysis. The polyp images are analyzed by a newly developed deep learning computer algorithm.

The Sun is an enigmatic star that produces the most powerful explosive events in our solar system - solar flares and coronal mass ejections. Studying these phenomena can provide a unique opportunity to develop a deeper understanding of fundamental processes on the Sun, and critically, to better forecast space weather.

The activities of the National Laboratory are focused on fundamental and applied research on the autonomous functionality and the control of road vehicles, aircraft and drones, robots and cyber-physical manufacturing systems. The main fundamental research topics are modelling, model reduction and identification, adaptive, robust, distributed and networked systems control. These areas are closely related to the applied research areas, which include environment perception and situation assessment, vehicle dynamics modelling and control, as well as testing and validation.

The aim of the research project

When controlling automated vehicles, it is essential that the control system has information about the state of the ego-vehicle and its environment.

Introduction

One of the cornerstones of the development of autonomous vehicles nowadays increasingly focused on research is that the vehicle control system is able to plan the path of the vehicle taking into account the static and dynamic objects of the environment. Environmental sensing is based on sensors based on a variety of principles, such as ultrasound, radar, lidar, or machine vision based camera systems.

With new hardware and artificial intelligence against skin cancer

PREdictor for HUman-RObot COllaboration (PREHUROCO) utilizes interactive technologies in a new innovative way to create a cobot independent pre-collision approach for reducing these cumulative delays. PREHUROCO technology creates a shared virtual reality workspace over the Internet/Intranet for humans and robots. The human operator will be digitally immersed into the real-time digital twin of the manufacturing cell by XR visualization and/or haptic feedback.

The HydroCobotics H2020 cascade consortium is coordinated by industrial robotics company Hepenix kft., while hydroponics company Green Drops Farm kft. is also a member. Within ELKH SZTAKI, the project is coordinated by Research Laboratory on Engineering & Management Intelligence research fellow Imre Paniti. The research and development project starts on the 1st of January, 2021 and presumably concludes on the 30th of September, 2021.

In the fight against COVID-19, manufacturing and distributing vital medical equipment became a major challenge. Unforeseen spikes in demand for essential medical supplies have been causing a greater urgency for supply chain optimisation and for deploying innovative approaches to scale up flexible and sustainable production methods.