Nathan Day

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About

Nathan Day is a pioneering researcher in the field of soft robotics, with a focus on enabling safe, compliant, and scalable robotic systems. His work addresses the fundamental challenges of controlling and sensing in large-scale, pneumatically actuated soft robots—machines that can safely interact with humans and environments without causing harm. Day’s most cited paper, “Configuration Estimation for Accurate Position Control of Large-Scale Soft Robots” (2018, 54 citations), defines the core problems of controlling these passively compliant, inflatable systems and proposes novel estimation methods for precise position control. His second highly cited work, “Scalable fabric tactile sensor arrays for soft bodies” (2018, 15 citations), tackles the critical need for integrated sensing in soft robots, introducing scalable, fabric-based tactile sensors that allow these machines to perceive their surroundings. Together, these contributions advance the practical deployment of soft robots in real-world applications, from collaborative manufacturing to assistive technologies. Day’s research is notable for bridging the gap between theoretical soft robotics and tangible, deployable systems, making him a key figure in the field’s evolution toward safer, more capable machines.