Global turmoil, terrorism and hybrid war has made cost-effective and energy-efficient surveillance of the critical infrastructure extremely important for public safety and critical functions. PROACTIF tackles the challenge by developing unmanned...
Efficient environment perception and reconstruction: Simplifying and compressing point clouds without the loss of meaningful information
Department in charge
In today's autonomous world, the transmission and interpretation of large amounts of information describing the environment is a key issue. The research aims to make self-driving cars, robots, and drones work more efficiently. This requires more...
The project aims to address the problem of the limitations of current Light Detection and Ranging (LIDAR) and camera technologies for autonomous driving. Traditional mechanical LIDAR systems are bulky, expensive, and require frequent maintenance, the...
AI based Fusion of Satellite/Airborne data for Biodiversity Change Characterization
Department in charge
Project objectives: With the support of the European Space Agency, HUN-REN SZTAKI and the Lechner Knowledge Centre (LTK) are collaborating to develop a new methodology for mapping and characterizing geographical areas based on the presence and...
B-prepared builds on a freely accessible massive collaborative knowledge base and data hub, demonstrating its usefulness via three demonstrator applications: a cooperative multiplayer VR serious game, simulating real disaster scenarios for the safest...
With technology rapidly enhancing and becoming more affordable, commercial and consumer drones have become increasingly popular since the beginning of the 21st century. They pose serious threats to safety (e.g. disturbances for airports and airplanes...
The project will further develop and optimise the road defect detection algorithm developed within ARNL. The algorithm uses a self-learning neural network, LiDAR and camera fusion to determine road surface deviations in front of vehicles that are...
The Multinational Capability Development Campaign (MCDC) Artificial Intelligence Supported by Sensor Fusion project was jointly organised by HUN-REN SZTAKI (Hungarian Research Network Computer and Automation Research Institute), the MH Military...
Scene analysis and reconstruction from incomplete spatial data
Department in charge
Due to the rapid progress of sensor technology, processing a large amount of incomplete 3D spatial data is becoming a critical issue. In environment perception tasks (e.g., remote surveillance, navigation of autonomous vehicles, medical diagnostics)...
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...
Bring back to the engineering students the results of research activities in the field of digital manufacturing. Modeling, analysis, virtual and augmented reality, as well as the role of the human workers in the factories have been among the main...
Multimodal feature fusion for establishing novel 3D saliency models
Department in charge
The project aims to process the data of novel 3D sensors (e.g. Microsoft Kinect, Lidar, MRI, CT) available in a wide range of application fields and to fuse them with 2D image modalities to build saliency models, which are able to automatically and...
