Maximilian Naumann
Papers
2
Total Citations
44
H-Index
2
About
Maximilian Naumann is a leading researcher in the field of cooperative autonomous systems, with a primary focus on motion planning for non-holonomic agents. His work bridges the gap between classical robotics and deep learning, particularly through the innovative application of Value Iteration Networks (VINs) to multi-agent coordination. Naumann’s major contribution lies in extending VINs to solve cooperative motion planning tasks under non-holonomic constraints, enabling multiple agents—such as automated vehicles—to plan paths that are not only reactive but truly interactive and anticipatory. This approach addresses one of the most challenging aspects of autonomous driving: safe and efficient cooperation in shared environments. His most-cited work, the open-source simulation framework **CoInCar-Sim** (2018, 40 citations), provides a critical platform for testing and validating cooperative driving algorithms, making it a valuable resource for the research community. By tackling the complexities of interaction between traffic participants, Naumann’s research has laid foundational groundwork for the next generation of automated vehicles, where cooperation is key to safety and efficiency.
Research Focus
Key Achievements
Top Papers
- 1
- 2