Dhiego Bersan
Papers
2
Total Citations
49
H-Index
2
About
Dhiego Bersan is a researcher specializing in robot navigation, semantic mapping, and computer vision, with a focus on enabling robots to better understand and interact with their environments. His work sits at the intersection of deep learning and robotics, where he has made meaningful contributions to the development of intelligent perception systems that go beyond traditional geometric representations of space. Bersan's most recognized contributions center on semantic map augmentation — a technique that enriches standard robot navigation maps with meaningful object-level information derived from visual and depth data. His 2020 paper, "Extending Maps with Semantic and Contextual Object Information for Robot Navigation," has accumulated 30 citations and builds upon an earlier 2018 framework that garnered 19 citations, demonstrating a clear and sustained research trajectory in this domain. His approach leverages deep neural networks for object detection and semantic classification, enabling robots to construct richer, more informative representations of their surroundings. This line of research is particularly relevant to the growing field of autonomous systems, where situational awareness and contextual understanding are critical for safe and efficient navigation. Bersan's work offers practical pathways for advancing robot autonomy in real-world, unstructured environments.
Research Focus
Key Achievements
Top Papers
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