<strong>Abstract</strong>: Robots that move through our world to solve real tasks are on the cusp of widespread adoption. But safe, reliable mobility remains out of reach. The next generation of mobile robots must feature more sensorimotor complexity than ever before to embody a diverse set of behaviors and modalities. My research program aims to uncover the design principles of high-performance, multimodal animal locomotion and use them to engineer machines with the agility, robustness, and economy of natural systems. In this talk, I’ll show how lizards harness a novel affordance for orientation control by swinging appendages like tails and limbs to generate inertial forces. I’ll introduce a reduced order modelling framework that connects models at two levels of complexity to provide both mechanistic principles and the details of how form affects function. This framework enabled design of tailed robots that harness inertial affordances as well as analysis of a diverse set of animals and machines with inertial reorientation capability. Finally, I’ll touch on a series of experiments with animals including insects and geckos that can inform the next generation of multifunctional robots by showing how body parts can be re-used creatively to enable multiple behaviors without unnecessary complexity. My future work will bring animal and robot designs into a unified framework that produces shared principles, reveals tradeoffs and synergies, and explains how components shape behavior.

<strong>Biosketch</strong>: <span lang=”EN”>Thomas Libby is a Postdoctoral Fellow at the University of Washington, working in collaboration with Sam Burden in Electrical Engineering and Tom Daniel in Biology. He received his doctoral degree and his bachelor’s degree in Mechanical Engineering from the University of California, Berkeley, where he was also the technical director of the Center for Interdisciplinary Bio-inspiration in Education and Research (CiBER). His research seeks design and control principles for locomotion, using a combination of model-based dimensional reduction and comparative experiments in animals and robots. He is the recipient of a WRF Innovation Postdoctoral Fellowship in Neuroengineering.</span>

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