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202337 https://hdl.handle.net/2286/R.2.N.202337 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2025 105 pages Masters Thesis Academic theses en Dutta, Prajjwal Yu, Xi Redkar, Sangram Das, Jnaneshwar Arizona State University Partial requirement for: M.S., Arizona State University, 2025 Field of study: Engineering Sea-level rise driven by climate change demands accurate data from sub-ice oceanenvironments, regions that are difficult to access using conventional technology. The project proposes a scalable robotic system comprising a mothership Autonomous Underwater Vehicle (AUV) carrying a swarm of low-cost passenger robots to explore these remote zones collaboratively. This thesis develops a modular simulation and control framework to coordinate such multi-Autonomous Underwater Vehicle (multi-AUV) systems under constraints of visibility, communication, and energy. Central to the framework is a six-degrees- of-freedom (6-DOF) dynamic model inspired by a thruster-driven blimp platform, offering realistic underwater motion representation, modular hardware compatibility and Hardware-in-the-loop testing capability. A real-time, optimization-based control strategy is implemented using Control Lyapunov Functions (CLFs) for goal convergence and Control Barrier Functions (CBFs) for safety enforcement, including collision avoidance and connectivity. These objectives are solved as a Quadratic Program (QP) by each agent, allowing scalable, distributed execution. To extend coordination to larger fleets, a visibility-aware algorithm based on a dy- namic minimum spanning tree is used to maintain essential communication links while reducing control effort. Simulation results using both high-fidelity and point-mass models demonstrate robust and scalable performance in cluttered, flow-influenced environments. The proposed system enables adaptive, safe coordination suitable for future deployment in under-ice or similarly extreme underwater domains. This work contributes a flexible and physically grounded control framework for multi-AUV coordination and supports the long-term goals of the MOTHERSHIP project. Robotics Electrical Engineering Autonomous Underwater Vehicles (AUVs) Connectivity Maintenance Control Barrier Functions (CBF) Control Lyapunov Functions (CLF) Multi-agent Systems Simulation and Modeling Connectivity-Aware Coordination and Control of Autonomous Underwater Vehicles in Environment Dynamics