Papers
28
Total Citations
411
H-Index
14
About
Henrik Ebel is a robotics and control systems researcher whose work sits at the intersection of multi-robot coordination, model predictive control, and autonomous systems. His research has made significant contributions to cooperative transportation, where groups of mobile robots collaborate to move objects through distributed control architectures. His 2020 paper on cooperative transportation schemes has garnered 48 citations, while his work on distributed nonlinear model predictive control for robot formations has attracted 41 citations, reflecting the field's strong interest in scalable, real-time optimization approaches for multi-agent systems. Ebel's contributions span both theoretical frameworks and experimental validation, notably comparing formation control strategies rooted in optimization and algebraic graph theory. Beyond ground robots, his research extends to aerial systems, including an LSTM-based UAV precision landing method and time-optimal trajectory planning for aerial manipulators, demonstrating impressive breadth. His exploration of Gaussian process regression for omnidirectional robot trajectory tracking further highlights his integration of machine learning with classical control theory. With over 270 cumulative citations and a consistent publication record across leading venues, Ebel has established himself as a productive contributor to intelligent robotic systems research, offering students and practitioners rigorous, experimentally grounded methods for tackling complex multi-robot coordination challenges.
Research Focus
Key Achievements
Top Papers
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- 7An LSTM‐based approach to precise landing of a UAV on a moving platform20 citations · 2022
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