AIFORS

ERA Chair in Artificial Intelligence for Robotics

 

 

AIFORS is a Horizon 2020 ERA Chair project which aims to create an ERA Chair in Artificial Intelligence for Robotics at the University of Zagreb Faculty of Electrical Engineering and Computing (UNIZG-FER). It will enable UNIZG-FER to attract an outstanding researcher and five team members to independently implement an ambitious research strategy in AI for robotics. This will open UNIZG-FER to a new research direction with a high potential for research outputs and technology innovation. The ERA Chair holder will establish and lead a Research Group for Artificial Intelligence for Robotics assigned to the Laboratory for Autonomous Systems and Mobile Robotics (LAMOR).


Visit to companies Protostar Labs...

The AIFORS team, professors Fabio Bonsignorio, Ivan Petrović and Ivan Marković, together with Juraj Peršić from Callirad d.o.o., went to Osijek to visit companies Protostar Labs and Orqa. Together with companies' representatives, they discussed possible cooperation and joint project proposals for relevant incoming calls.

You can find more about the visit in the detailed news content.

 

Protostar Labs d.o.o. is a Croatian software development company founded in 2019 and focused on developing advanced solutions based on artificial intelligence and computer vision. They specialize in the development of industrial production automation solutions that use artificial intelligence to automatically recognize and classify products, and detect errors and malfunctions.

Croatian company Orqa d.o.o. was founded in 2018 with the mission to innovate products across the FPV drones industry. They are focused on innovating and developing all parts of the FPV technology stack as they strive to become the World’s number one technology provider for First Person View (FPV) and advanced Remote Reality (RR) applications by developing enabling technology for next-generation vision systems.  

News list

SOCIAL MEDIA

 


PROJECTS

 

 

 


Funding

 

This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Grant Agreement No. 952275