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From the 1 of 5 linked papers with an AI index.

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5 papers

eess.SY2026

Mixed Bernstein-Fourier Approximants for Optimal Trajectory Generation with Periodic Behavior

Liraz Mudrik, Sean Kragelund, Isaac Kaminer

The paper proposes a mixed Bernstein-Fourier approximation framework for generating optimal trajectories that exhibit periodic behavior, providing convergence proofs, error analysi…

math.OC2026

Saddle Point Evasion via Curvature-Regularized Gradient Dynamics

Liraz Mudrik, Isaac Kaminer, Sean Kragelund +1

Nonconvex optimization underlies many modern machine learning and control tasks, where saddle points pose the dominant obstacle to reliable convergence in high-dimensional settings…

math.OC2026

Prescribed-Time Distributed Generalized Nash Equilibrium Seeking

Liraz Mudrik, Isaac Kaminer, Sean Kragelund +1

Safety-critical multi-agent systems, from cooperative guidance to collision avoidance, must often reach a coordinated decision by a hard deadline rather than merely converge to one…

math.OC2026

Optimization via a Control-Centric Framework

Liraz Mudrik, Isaac Kaminer, Sean Kragelund +1

Optimization plays a central role in intelligent systems and cyber-physical technologies, where speed and reliability of convergence directly impact performance. In control theory,…

eess.SY2026

Multi-UAV Trajectory Optimization for Bearing-Only Localization in GPS Denied Environments

Alfonso Sciacchitano, Liraz Mudrik, Sean Kragelund +1

Accurate localization of maritime targets by unmanned aerial vehicles (UAVs) remains challenging in GPS-denied environments. UAVs equipped with gimballed electro-optical sensors ar…