Patrick Gruber
Papers
1
Total Citations
3
H-Index
1
About
Patrick Gruber is a leading researcher in automotive engineering, with a primary focus on vehicle dynamics, automated driving, and mobile robotic systems. His work bridges the gap between theoretical control systems and real-world experimental validation, particularly in the domain of path following control for scaled robotic vehicles. Gruber’s major contributions include the design and experimental validation of deep reinforcement learning-based controllers for path following, demonstrating how scaled platforms can serve as effective test benches for automated driving functions. His most-cited paper, "Modeling, Positioning, and Deep Reinforcement Learning Path Following Control of Scaled Robotic Vehicles: Design and Experimental Validation" (2024), has already garnered 3 citations, highlighting its emerging impact. This work is notable for integrating modeling, positioning, and advanced control strategies, offering a cost-effective and repeatable approach to developing autonomous vehicle technologies. Gruber’s research is instrumental in advancing the practical deployment of automated driving systems, making him a key figure in the evolution of intelligent transportation and robotic mobility.
Research Focus
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Top Papers
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