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About

Hany Nasry is a robotics researcher focused on advancing mobile robot autonomy, particularly in path planning and state estimation under uncertainty. His work centers on two key areas: improving real-time path planning algorithms and developing robust position estimation methods for unmanned ground vehicles (UGVs) operating in hazardous environments. Nasry's most cited paper, "ARA*+: Improved Path Planning Algorithm Based on ARA*" (2012, 11 citations), enhances the Anytime Repairing A* algorithm to guarantee smoother robot trajectories under time constraints—a critical improvement for real-world deployment. He has made significant contributions to stochastic position estimation, introducing the Euler-Maruyama algorithm (2019, 7 citations) and the Milstein algorithm (2021, 4 citations) to model white noise and time delays in teleoperated systems. His 2023 work applies the Euler-Maruyama method to nuclear emergency and security scenarios (4 citations), demonstrating practical impact in high-stakes fields. Nasry's research bridges theoretical stochastic differential equations with tangible applications in military, industrial, and nuclear contexts, offering students a clear example of how mathematical modeling directly enhances robot reliability in dangerous, unstructured environments.