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About

Frank Saunders is a pioneer in the field of soft robotics, focusing on the computational design and control of bio-inspired, compliant machines. His research centers on developing efficient locomotion strategies for soft-bodied robots—machines without rigid joints—by leveraging evolutionary algorithms and dynamic simulation. Saunders’s major contributions include demonstrating that genetic algorithms can effectively discover control schemes for soft robots in simulated environments, as shown in his most cited work, “Evolving soft robotic locomotion in PhysX” (47 citations). He further advanced the field by validating these simulated gaits through physical experiments, as detailed in “Experimental verification of soft-robot gaits evolved using a lumped dynamic model” (33 citations). His work on modeling soft-bodied arthropod locomotion using inverse dynamics (41 citations) has provided foundational insights into the mechanics of compliant movement. Saunders also developed a methodology for converting coarse dynamic simulations into manufacturable designs, bridging the gap between theory and practice. His research has significantly reduced the time and cost of soft robot development, making him a key figure in the growing field of soft robotics.