Abstract: Leveraging the capabilities provided by their deformable bodies, continuum soft robots promise to have a disruptive impact on several fields of science, industry, and society. In the past decade, substantial progress has been made in developing soft robotic platforms, but significantly less attention has been devoted to the control challenge. Today, soft robotic systems still need a low-level artificial brain that can make them execute precise motions and eventually exploit the intelligence embedded in their complex mechanical structures. In this talk, I will briefly introduce this grand challenge within the soft robotic field and then introduce the model-based view of its solution. I will show how simplified models can be combined with nonlinear control theory, leading to precise and dynamic task execution. I will then discuss how these techniques can be combined with data and machine learning.
Bio: Cosimo Della Santina is Assistant Professor at TU Delft and Research Scientist at the German Aerospace Institute (DLR). He received his Ph.D. in robotics (cum laude, 2019) from the University of Pisa. He was a visiting Ph.D. student and a postdoc (2017 to 2019) at the Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT). He was a senior postdoc (2020) and guest lecturer (2021) at the Department of Informatics, Technical University of Munich (TUM). Cosimo has been awarded euRobotics Georges Giralt Ph.D. Award (2020), the “Fabrizio Flacco” Young Author Award of I-RAS (2019), and he has been a finalist for the European Embedded Control Institute Ph.D. award (2020). He is PI for TU Delft of the European Projects Natural Intelligence and EMERGE, co-director of the Delft AI Lab SELF, and involved in a number of Dutch projects. His research interest is in motor intelligence of physical systems, focusing on elastic and soft robots.
This presentation will be given through zoom, please join us in 2405 Siebel Center for Computer Science
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[zoom link TBD]
Pizza will be served following the presentation.