Poziv na predavanje: Geometric and end-to-end robot vision-based control

Bio: François Chaumette is an Inria senior research scientist at Irisa in Rennes. He received a PhD in Computer Science from the University of Rennes 1 in 1990. His research interests include robotics and computer vision, especially visual servoing and active perception. He supervised more than 30 PhD students and published over 300 journal or conference papers, with the 2002 Best IEEE Transactions on Robotics and Automation Paper Award, the 2019 Best IEEE Robotics and Automation Letters Paper Award, and the 2020 Best IEEE Robotics and Automation Magazine Paper Award.
He was Founding Senior Editor of the IEEE Robotics and Automation Letters, member of the Editorial Board of the Int. Journal of Robotics Research, program co- chair of the IEEE Int. Conf. on Robotics and Automation in 2020, and served recently as Senior Editor of the IEEE Transactions on Robotics. He was a panel member for the ERC PE7 Consolidator grants in 2013, 2015, 2017 and 2019. He was recently involved in the H2020 EU Comanoid project. He is IEEE Fellow since 2013.

Abstract: As for humans and most animals, vision is a crucial sense for a robot to interact within its environment. Vision-based robot motion control, also named visual servoing, is a general approach to close the perception-action loop. The aim of this talk is to provide a comprehensive state of the art on the basic concepts, methodologies, and applications. In a first part, the traditional approach based on geometric visual features, such as image points, image moments, or camera-object pose will be described. The more recent end-to-end approach that directly uses the image content without any image tracking nor matching process will be also considered, providing a link to CNN modern methods that use the same inputs.