Mark Karpenko

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About

Mark Karpenko is a leading figure in optimal control and trajectory optimization, with a particular focus on enabling complex autonomous maneuvers for both robotic systems and spacecraft. His work bridges foundational theory and practical flight applications, making significant contributions to collision-free motion planning and high-performance attitude control. A key contribution is his novel approach to smooth proximity computation for multiple robotic manipulators, which leverages Karush-Kuhn-Tucker (KKT) conditions to efficiently compute distances between line-swept sphere bounding volumes, enabling robust, collision-free optimal control in cluttered environments. This work, which has garnered 11 citations, provides a critical tool for multi-agent coordination. Demonstrating the real-world impact of his research, Karpenko led the development of fast attitude maneuvers for NASA’s Lunar Reconnaissance Orbiter (LRO), a spacecraft launched in 2009 that continues to map the Moon. By applying Birkhoff pseudospectral theory and Hamiltonian programming, he enabled rapid, fuel-efficient reorientation maneuvers for this operational mission, a landmark achievement in practical flight application of advanced optimal control theory. This work has already received 7 citations and showcases his unique ability to translate sophisticated mathematical methods into tangible, mission-critical solutions for space exploration.