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Anh V. Nguyen’s research lies at the intersection of robotic manipulation, locomotion, and surgical robotics, with a focus on enabling robots to interact intelligently with complex, unstructured environments. A central contribution is his work on task-oriented grasping, where he pioneered a method that reorients objects to a “nominal pose”—the precise configuration required for a specific manipulation task. This approach, detailed in his 2016 paper (25 citations), combines visual 6D pose estimation with grasp planning, directly linking perception to functional action. In locomotion, Nguyen advanced legged robotics by developing a vision-based foothold contact reasoning system that uses curved surface patches to model foot-terrain interactions, a critical step for stable movement on rough terrain (2017, 22 citations). His earlier work includes a fast heuristic algorithm for the planar find-path problem (1984, 10 citations), which uses linked cones to map free space—a foundational contribution to motion planning. More recently, he has applied hybrid data-driven and analytical modeling to kinematic control of tendon-driven surgical tools (2020), addressing nonlinearities inherent in minimally invasive surgery. With over 90 total citations, Nguyen’s work bridges classical robotics theory and modern data-driven methods, offering practical solutions for grasping, walking, and surgical robots.