Simon Williams

Papers

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About

Simon Williams is a robotics researcher specializing in autonomous underwater vehicle (AUV) navigation and motion planning, with a particular focus on dynamic, real-world environments. His most cited work, "Dynamic Target Driven Trajectory Planning using RRT" (2019, 5 citations), addresses the critical challenge of guiding an AUV back to a moving recovery vessel using only passive, angle-only sensors. This contribution is notable for integrating rapidly-exploring random tree (RRT) algorithms with constrained sensing, enabling robust trajectory generation under uncertainty. Williams’ research bridges the gap between theoretical path planning and practical deployment in marine robotics, where communication and sensor limitations are severe. His work has implications for underwater search-and-rescue, oceanographic surveying, and autonomous naval operations. Though early in his career, Williams has established a focused niche in sensor-limited, dynamic target tracking—a problem of growing importance as AUVs are tasked with longer, more autonomous missions. His approach demonstrates how classical planning algorithms can be adapted to real-world constraints, making his research valuable for students and engineers working on field-deployable robotic systems.