Soft-bodied robots present a compelling solution for navigating tight spaces and interacting with unknown obstacles, with potential applications in inspection, medicine, and AR/VR.  Yet, even after a decade, soft robots remain largely in the prototype phase without scaling to the tasks where they show the most promise. These systems are difficult to design and control because their morphology is coupled with both their actuation and the environment, creating a large joint space that cannot be exhaustively explored through prototype iteration. Soft roboticists need new tools to repeatably develop systems that leverage deformability and contact. Dr. Sedal will first present recent work on jointly optimizing the design and control of soft robots in simulation. Through a combination of reduced-order finite element simulation and reinforcement learning, this work trained soft-legged, crawling robots, achieving performance that surpassed expert baselines and transferred to real physical results. Second, Dr. Sedal will present work on deformable acoustic tactile sensors and design with auxetic meta-materials. The research presented here will enable engineering tools for development of intelligent structures with high compliance for high-contact settings, taking soft robots out of the laboratory and into the world.

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