Stanford AA274A Principles of Robotic Autonomy | Autumn 2019 | Multi-Sensor Fusion

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education Lecture 20 — Multi-Sensor Perception and Sensor Fusion Note: This lecture was recorded as part of the 2019 edition of the course. Course content, structure, assignments, and other materials may have changed since this recording. The course links below point to the most recent edition and may therefore differ from what is presented in the video. Read the companion textbook, Principles of Robot Autonomy, free online: https://porabook.com Follow along with the latest course schedule and syllabus: https://stanfordasl.github.io/PoRA-I Speaker: Prof. Daniel Watzenig Dr. Daniel Watzenig is a Full Professor at Graz University of Technology, Austria, where he leads the Multi-Sensor Perception research group, and Chief Technology Officer of Virtual Vehicle Research GmbH, an applied research center for sustainable mobility in Graz. He received his master’s and doctoral degrees in electrical engineering from Graz University of Technology in 2002 and 2006. His research focuses on sensing and control of autonomous vehicles, multi-sensor perception and sensor fusion, and decision making under uncertainty. He is Editor-in-Chief of the SAE International Journal of Connected and Automated Vehicles, an IEEE Distinguished Lecturer on autonomous vehicles, and founder of the Autonomous Racing Graz team. Since 2019 he has been a guest lecturer at Stanford University, teaching multi-sensor perception, data fusion, and software for autonomous systems. Instructor: Prof. Marco Pavone, Associate Professor of Aeronautics and Astronautics, Director of Autonomous Vehicle Research at NVIDIA Dr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University and a Senior Director of Autonomous Vehicle Research at NVIDIA. Prior to joining Stanford, he was a Research Technologist in the Robotics Section at NASA’s Jet Propulsion Laboratory. Dr. Pavone received his Ph.D. in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His research focuses on the analysis, design, and control of autonomous systems, with particular emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He has been recognized with numerous awards, including the Presidential Early Career Award for Scientists and Engineers from President Barack Obama, the Office of Naval Research Young Investigator Award, the NSF CAREER Award, the NASA Early Career Faculty Award, the IEEE Kiyo Tomiyasu Award, the CSS Award for Technical Excellence in Aerospace Control, and the Early-Career Spotlight Award from the Robotics Science and Systems Foundation. Full playlist: https://www.youtube.com/playlist?list=PLR9iNyexfIkk #StanfordOnline #RobotAutonomy #Robotics #PhysicalAI