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Abstract: Simulation-to-reality transfer is an emerging approach that enables robots to develop skills in simulated environments before applying them in the real world. This method has catalyzed numerous advancements in robot learning, from locomotion to agile flight. In this talk, I will explore simulation-to-reality transfer through the lens of evolutionary biology, drawing parallels with the function of the mammalian neocortex. By reframing this technique in the context of biological evolution, we can uncover novel research questions and explore how simulation-to-reality transfer can evolve from an empirically driven process to a scientific discipline.

Bio: Antonio Loquercio is an assistant professor at the University of Pennsylvania. He received his Ph.D. and M.Sc. from UZH and ETH Zurich in 2021 and 2017. His research interests include learning-based robotics, computer vision, and machine learning. His work includes seminal results on simulation to real-world transfer for sensorimotor control. He is the recipient of the 2017 ETH Medal for Outstanding Master Thesis, the Best System Paper Award at the Conference on Robot Learning (CORL) 2018, the RSS’20 Best Paper Award Honorable Mention, and the T-RO’20 Best Paper Award Honorable Mention. His article on superhuman drone racing was featured on Nature's cover. He received the Georges Giralt Ph.D. Award, the most prestigious award for Ph.D. dissertations in robotics in Europe.