Arman Asgharpoor Golroudbari
Papers
3
Total Citations
27
H-Index
3
About
Arman Asgharpoor Golroudbari is an emerging researcher whose work sits at the compelling intersection of deep learning and autonomous navigation. His most recognized contribution is a comprehensive review of state-of-the-art deep learning methodologies applied to autonomous systems, a work that has garnered notable attention within the research community, accumulating citations across multiple indexed venues since its publication in 2023. This review systematically examines how modern artificial intelligence frameworks are being leveraged to solve some of the most challenging problems in autonomous navigation, including signal processing, attitude estimation, obstacle detection, scene perception, and path planning. By synthesizing end-to-end deep learning approaches and evaluating their practical applicability, Golroudbari has provided a valuable reference point for both newcomers and seasoned researchers navigating this rapidly evolving field. His ability to distill complex methodological landscapes into accessible, structured analyses speaks to a rigorous academic sensibility. Though still early in his career, his work demonstrates a clear commitment to advancing the theoretical and applied foundations of intelligent autonomous systems, positioning him as a researcher worth following as the field continues to mature.
Research Focus
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Top Papers
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