| Date: | 05 October 2026, 14:00 – 15:30 (CET) | Price: | Free (for eligible participants) | |
| Format: | AI:AT Webinar, ONLINE (Zoom) | Target audience: | Industry, public admin, academia | |
| Language: | English | Organizer: | AI:AT |
How can robots see, decide, and act? This 3-part webinar series shows how AI connects visual perception, world understanding, planning, and control - revealing how robotic systems move from raw sensor data to intelligent action in real environments.
This webinar series offers an accessible introduction to AI-based robotic vision and control, with a strong focus on how perception, planning, and action are integrated into intelligent robotic systems. Designed for a broad audience, the series will break down complex ideas to accessible explanations and examples, without requiring a deep technical background.
The final session of the webinar series connects vision and reasoning to action, exploring how robotic systems are built end to end. It introduces task and motion planning (TAMP) as the bridge between high-level symbolic reasoning and low-level geometric execution, covering architectural strategies from separate and interleaved approaches to fully integrated formulations - and the trade-offs between modularity, computational complexity, and robustness. The session then examines robotic control strategies, contrasting reinforcement learning and imitation learning and how robots acquire and adapt skills in dynamic environments. Bringing the series full circle, the closing session offers a systems-level view of how perception, planning, and control are combined into robust robotic solutions. Real-world examples from industrial automation - including production, logistics, mining, and forestry - illustrate how these technologies come together in practice, followed by key takeaways and an open discussion with the audience.
This session brings together the concepts introduced in From Computer Vision to Robotic Understanding and Learning, Perception, and Robotic Decision Intelligence into a complete systems perspective.
Target audience
This webinar is open and free of charge for all participants from academia, industry, and public administration from EU and/or EuroHPC JU member countries.
Entry level & prerequisites
Basic - no previous experience required.
Agenda
- Task and motion planning (TAMP) (20 mins): Concepts and architectures: separate, interleaved, and combined planning; linking symbolic task reasoning with geometric motion planning.
- Robotic control strategies (20 mins): Reinforcement learning vs. imitation learning; how robots acquire skills and adapt to dynamic environments.
- Building integrated robotic systems (20 mins): Systems-level view of how perception, planning, and control components are combined into robust robotic solutions for weakly controlled or dynamic environments.
- Applied examples and closing discussion (20 mins): Examples from industrial automation domains such as production, logistics, mining, and forestry, followed by key takeaways and audience questions
Speakers
Dr. Csaba Beleznai (AIT Austrian Institute of Technology)
Dr. Csaba Beleznai is a Senior Scientist at the AIT Austrian Institute of Technology, bringing over 26 years of expertise in Computer Vision, Machine Learning, and Deep Learning. His research focuses on solving complex 3D object pose estimation tasks essential for robotic navigation and object manipulation, as well as developing advanced vision-based perception models for broader robotic applications. Dr. Beleznai holds an M.S. from the Technical University of Ilmenau (Germany) and a Ph.D. in Physics from Claude Bernard University, Lyon (France). Committed to education, he regularly lectures at various summer schools and universities, including FH Wiener Neustadt and FH Technikum Wien. You can connect with him on Linkedin via: https://www.linkedin.com/in/csaba-beleznai-78b3821/
Dr. Patrik Zips (AIT Austrian Institute of Technology)
Dr. Patrik Zips is a Senior Scientist at the AIT Austrian Institute of Technology, working in the Center for Vision, Automation and Control. He has over 15 years of experience in robotic task and motion planning, with a strong focus on developing algorithms that are robust and feasible in real-world settings involving highly nonlinear dynamics. His research bridges theory and practice, with many of his methods deployed and validated in AIT’s large-scale robotics lab, an experimental environment for autonomous utility machines operating in challenging outdoor conditions. Dr. Zips holds a PhD in Automation and a Master’s degree in Electrical Engineering from TU Wien. LinkedIn: https://www.linkedin.com/in/patrik-zips-b95523286/
Language
English
Date, time, and location
05.10.2026, 14:00 – 15:30 (CET), LIVE ONLINE WEBINAR (Zoom)
Registration
Registration is required, the link to the registration form can be found on the top of this page in the menu on the left. Please register with your official institutional email address to prove your affiliation.
You will get the Zoom link in the automatic confirmation by email (subject starting with "[Indico] Registration"), please check your Spam/Junk folders). We will also send 1–2 reminders before the webinar.
Please do not hesitate to contact us at training@ai-at.eu if you have any questions.
Organizers
This webinar is organized by AI Factory Austria AI:AT.
Acknowledgements
AI Factory Austria AI:AT has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101253078. The JU receives support from the Horizon Europe Programm of the European Union and Austria (BMIMI / FFG).
