Probabilistic and Machine Learning Approaches for Autonomous Robots and Automated Driving
Explore a 51-minute keynote address by Prof. Wolfram Burgard, a renowned expert in robotics and AI, on probabilistic and machine learning approaches for autonomous robots and automated driving. Delve into the challenges of robust environmental perception and action execution for autonomous systems. Discover how the probabilistic approach to robotics provides a rigorous statistical methodology for state estimation. Learn about extending this approach with cutting-edge machine learning technologies to develop more robust autonomous systems. Gain insights into the potential applications of these advancements in everyday life, presented by a distinguished researcher known for his contributions to mobile robot navigation and simultaneous localization and mapping.