Amr S. Mahmoud
Papers
2
Total Citations
3
H-Index
1
About
Amr S. Mahmoud is a researcher focused on advancing autonomous vehicle control, particularly for complex, unstable systems like truck-trailer wheeled robots. His work centers on developing intelligent algorithms for challenging maneuvers, such as reverse parking and trajectory following, which are notoriously difficult even for experienced human drivers. By integrating reinforcement learning techniques—including Recurrent Proximal Policy Optimization and trajectory state model-based approaches—Mahmoud aims to replace manually designed control policies with scalable, adaptive solutions that ensure system stability, steering precision, and collision avoidance. His 2023 paper on automatic parking has garnered 2 citations, while his 2024 work on reverse driving continues to build on these foundations. Though early in his citation impact, Mahmoud’s contributions address a critical gap in autonomous logistics and robotics, offering promising pathways for safer, more efficient maneuvering of articulated vehicles in constrained environments. His research is particularly relevant for students and engineers interested in the intersection of reinforcement learning, robotics, and real-world control challenges.
Research Focus
Key Achievements
Top Papers
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