Tiago Dias

University of Coimbra, University of Lisbon

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Total Citations

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About

Tiago Dias is a researcher at the forefront of robotics and computer vision, with a particular focus on omnidirectional perception and augmented reality for autonomous systems. His work bridges the gap between advanced imaging technologies and practical robotic applications, notably through the development of frameworks that integrate non-central catadioptric cameras with augmented reality for enhanced robot navigation. Dias’s pioneering research includes the introduction of OmniDRL, a deep reinforcement learning approach for robust pedestrian detection using omnidirectional cameras, demonstrating how non-perspective imaging can overcome traditional field-of-view limitations. With key contributions cited in works like "Augmented reality on robot navigation using non-central catadioptric cameras" (7 citations) and his involvement in the SocRob@Home project, Dias has established himself as a contributor to socially assistive robotics and intelligent perception systems. His work is particularly relevant for researchers exploring the intersection of deep learning, reinforcement learning, and wide-angle vision for real-world robotic autonomy.