Paul Sassaman

The University of Texas at Arlington, Hanover College

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About

Paul Sassaman’s research bridges the critical gap between human motor function and intelligent robotic systems, with a primary focus on rehabilitation engineering and autonomous aquatic navigation. His most impactful work centers on the MAGNI system, a pioneering framework that integrates the Barrett WAM Arm with video gaming to create self-managed, robot-aided physical therapy. By enabling real-time patient-game interaction and force analysis, Sassaman’s research allows clinicians to monitor rehabilitation progress and quantify upper extremity motor recovery with unprecedented precision—his foundational paper on this topic has garnered 13 citations, establishing a benchmark in tele-rehabilitation. Beyond healthcare, Sassaman has ventured into autonomous systems with CataBotSim (2024), a high-fidelity Unity3D-based aquatic simulator designed for testing perception and navigation pipelines in autonomous surface vehicles, addressing a critical lack of realistic testing environments in marine robotics. His work demonstrates a rare versatility, applying advanced control and sensing techniques to both human-centered rehabilitation and field robotics. For students and researchers, Sassaman’s contributions exemplify how robotic systems can be repurposed across domains—from restoring motor function in patients to enabling robust autonomy in unpredictable aquatic environments.