Samer Hanoun

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About

Samer Hanoun is a leading researcher in autonomous systems, specializing in the path planning and motion control of unmanned aerial vehicles (UAVs) and ground mobile robots. His work addresses critical challenges in real-world deployment, particularly for multirotor UAVs operating in dynamic, windy environments and supporting mobile ground vehicles. Hanoun’s most cited paper, “Path Planning of Unmanned Aerial Vehicles (UAVs) in Windy Environments” (2022, 55 citations), introduces novel techniques for pursuing ground moving targets under variable conditions, a key enabler for reconnaissance and surveillance missions. His follow-up work on UAV path planning for look-ahead coverage support (2021, 24 citations) tackles the complexities of coordinating aerial and ground assets with unpredictable velocity profiles. Demonstrating versatility, Hanoun also applies deep imitation learning to local motion planning for ground robots (2018), using only monocular RGB camera inputs and expert demonstrations to achieve robust navigation. With a growing citation impact, Hanoun’s research bridges theoretical algorithms and practical autonomy, offering scalable solutions for search-and-rescue, logistics, and defense applications. His contributions are shaping the next generation of intelligent, cooperative robotic systems.