Solmaz Torabi

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About

Solmaz Torabi is a researcher whose work lies at the intersection of robotics, optimization, and underwater vehicle coordination. Her primary research areas include multi-vehicle motion planning, mixed integer nonlinear programming (MINLP), and communication-constrained autonomous systems. Her most notable contribution is a pioneering framework for the fixed path coordination of multiple underwater vehicles under acoustic communication constraints. In her highly cited 2015 paper, which has garnered 25 citations, she introduced a discrete-time, distributed receding horizon mixed integer nonlinear programming (RH-MINLP) approach. This work directly addresses the critical challenge of enabling multiple autonomous underwater vehicles (AUVs) to operate effectively in environments where acoustic communication is limited and unreliable. By applying advanced MINLP techniques to multi-vehicle motion planning, Torabi provided a robust solution for coordinating vehicle trajectories while respecting strict communication and timing constraints. Her research has significant implications for oceanographic exploration, underwater surveillance, and environmental monitoring, where teams of AUVs must work in concert. Torabi’s contributions demonstrate a sophisticated blend of theoretical optimization and practical robotic application, marking her as a key figure in advancing autonomous underwater systems.