témavezető: Fenech Kristian Arian
helyszín (magyar oldal): Eötvös Loránd Tudományegyetem helyszín rövidítés: ELTE
A kutatási téma leírása:
Effective human-machine collaboration needs effective communication and robust representations. The aim of this project is to investigate how machines can learn to perceive and understand complex and pragmatic signs from humans as they navigate and perform tasks in highly complex and dynamic environments. Machines in these cases will need to be able to estimate attributes which give rise to infomation regarding a persons internal state, their intentions and goals. As well as there external state, their motion now and in the near future. In addition, how human and machine can effectively communicate can be altered both by physical limitations enforced due to certain activities or environmental conditions, however the machine must not fail in its interpretation given this altered representations. This requires work towards the development of rich digitial representations of objects, environments and people which can be used and updated in real-time forming expressive digital-twins which may be used in a wide variety of use cases such as path planning and optimisation in factories, security and safety, and virtual training environments.
előírt nyelvtudás: angol további elvárások: • Strong knowledge of linear algebra, machine learning and python programming.
• Knowledge of robotic systems is a bonus
• Knowledge in computer graphics and common tools such as Unity3D/Blender is beneficial but not essential
felvehető hallgatók száma: 3
Jelentkezési határidő: 2024-05-31
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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