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About

Yesim A. Baysal is a robotics researcher whose work centers on the modeling, simulation, and optimization of snake robots — biomimetic systems designed to replicate the remarkable locomotion capabilities of their biological counterparts. Her research addresses some of the most pressing challenges in this field, including kinematic and dynamic modeling of wheel-less snake robots in MATLAB/Simulink, where she has investigated the critical role of ground friction in enabling realistic locomotion behavior. A distinctive strength of Baysal's work lies in her application of advanced optimization techniques to solve energy efficiency problems in untethered snake robots. She has employed the symbiotic organism search algorithm and multi-objective optimization frameworks — including a fast non-dominated sorting variant — to identify optimal gait parameters, a largely underexplored area within snake robotics. Her research also extends to adaptive locomotion strategies that allow robots to function effectively across varying environmental conditions, bridging the gap between biological snake motion and practical robotic implementation. With publications accumulating over 30 citations collectively, Baysal's contributions offer foundational tools for researchers working on search-and-rescue robotics, hazardous environment exploration, and bio-inspired autonomous systems, making her an emerging voice in intelligent robotics research.