Lecture Series: Probabilistic and Deep Learning Techniques for Robot Navigation and Automated Driving

Probabilistic and Deep Learning Techniques for Robot Navigation and Automated Driving

For autonomous robots and automated driving, the capability to robustly perceive environments and execute their actions is the ultimate goal. The key challenge is that no sensors and actuators are perfect, which means that robots and cars need the ability to properly deal with the resulting uncertainty. In this presentation, I will introduce the probabilistic approach to robotics, which provides a rigorous statistical methodology to deal with state estimation problems. I will furthermore discuss how this approach can be combined using state-of-the-art technology from machine learning to deal with complex and changing real-world environments.

About Prof. Dr. Wolfram Burgard

Prof. Dr. Wolfram Burgard is a distinguished Professor of Robotics and Artificial Intelligence at the University of Technology Nuremberg where he also serves as Founding Chair of the Engineering Department. Previously, he held the position of Professor of Computer Science at the University of Freiburg from 1999 to 2021, where he established the renowned research lab for Autonomous Intelligent Systems.  His expertise lies in artificial intelligence and mobile robots, focusing on the development of robust and adaptive techniques for state estimation and control. Wolfram Burgard's achievements include deploying the first interactive mobile tour-guide robot, Rhino, at the Deutsches Museum Bonn in 1997. He and his team also developed a groundbreaking approach that allowed a car to autonomously navigate through a complex parking garage and park itself in 2008. In 2012, he and his team developed the robot Obelix that autonomously navigated like a pedestrian from the campus of the Faculty of Engineering to the city center of Freiburg.  Wolfram Burgard has published over 350 papers and articles in robotic and artificial intelligence conferences and journals. Additionally, he co-authored the two books “Principles of Robot Motion - Theory, Algorithms, and Implementations” and “Probabilistic Robotics”. In 2009, he was honored with the Gottfried Wilhelm Leibniz Prize, the most prestigious research award in Germany.  He is a member of the Heidelberg Academy of Sciences and the German Academy of Sciences Leopoldina.