Matthias Gerdts

Universität der Bundeswehr München

Papers

11

Total Citations

182

H-Index

7

About

Matthias Gerdts is a prominent applied mathematician and control engineer whose research sits at the intersection of optimal control theory, robotics, and autonomous systems. His most influential contributions center on trajectory optimization and collision avoidance, particularly developing mathematically rigorous frameworks for guiding robots and vehicles through complex, obstacle-laden environments. His 2012 paper on path planning and collision avoidance for robots, which garnered 56 citations, established a foundational optimal control formulation using linear programming arguments to generate the fastest collision-free trajectories—an approach he subsequently extended to welding robots and automotive applications. Gerdts has made significant methodological contributions through his development of nonsmooth Newton's methods for solving discretized optimal control problems with state and control constraints, earning 41 citations and providing practitioners with powerful numerical tools. His work on linear model-predictive control for mobile robots, bilevel optimal control, and reachable set computation further demonstrates his breadth across theoretical and applied domains. More recently, he has tackled multi-agent scenarios involving interacting vehicles using generalized Nash equilibrium frameworks. Through differential-algebraic equation modeling and sensitivity-based real-time control strategies, Gerdts continues advancing the mathematical foundations essential for safe, efficient autonomous systems in industrial and automotive settings.

Research Focus

Key Achievements

7
H-Index
11
Papers
182
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Path planning and collision avoidance for robots
56 citations · 2012
📈 Most Prolific Year: 2020 (4 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Universität der Bundeswehr München

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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