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About

Hande Y. Benson is a researcher specializing in mathematical programming and its applications to multi-vehicle motion planning, with a particular focus on coordinating autonomous systems under real-world communication constraints. Her work sits at the intersection of optimization theory and robotics, leveraging sophisticated techniques such as Mixed Integer Nonlinear Programming (MINLP) and receding horizon frameworks to solve complex, computationally demanding coordination problems. Benson's most significant contributions center on generating time-optimal velocity profiles for groups of path-constrained vehicles — including underwater autonomous systems — that must maintain communication connectivity while navigating toward fixed goals. Her research has progressively evolved from centralized formulations to decentralized frameworks, reflecting the practical demands of scalable, real-world robotic deployments. Notable work includes her 2015 paper introducing a distributed RH-MINLP framework for underwater vehicles operating under acoustic communication constraints, which has garnered 25 citations, and her 2013 study addressing robustness under stochastic communication conditions. Collectively, her publications have accumulated over 85 citations, demonstrating meaningful influence within the robotics and optimization communities. Students and researchers working in autonomous systems, multi-agent coordination, or applied mathematical programming will find her contributions foundational to understanding how rigorous optimization methods can be practically applied to dynamic, communication-aware robotic systems.