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About

Esen Yel is a researcher advancing the frontiers of resilient and autonomous robotics, with a focus on planning and control under degraded and uncertain conditions. Her work is particularly impactful in the domain of Unmanned Aerial Vehicles (UAVs) and heterogeneous robotic teams. A key contribution is the development of meta-learning-based frameworks that enable UAVs to proactively adapt to unforeseen challenges like actuator faults, system failures, and external disturbances, ensuring robust trajectory tracking and safety. Her influential paper, "A Meta-Learning-based Trajectory Tracking Framework for UAVs under Degraded Conditions," has garnered 12 citations, underscoring its relevance. Yel also addresses energy-aware persistent control for heterogeneous aerial and ground systems, optimizing task completion under energy constraints. Her research extends to safe planning in communication-limited environments, where robots rely on intermittent information. By integrating learning-enabled methods with proactive online planning, Yel's work provides critical solutions for real-world deployment of autonomous systems, making her a notable contributor to the fields of resilient robotics and intelligent control.