Catarina Silva

Instituto Superior de Gestão, University of Coimbra

Papers

Total Citations

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About

Catarina Silva is a researcher whose work spans robotics, neural architectures, and artificial intelligence, with a particular focus on the application of machine learning techniques to autonomous mobile systems. Her most recognized contribution, "MONODA: a neural modular architecture for obstacle avoidance without knowledge of the environment" (2000), introduced an innovative approach to robotic navigation in unknown environments. By employing cooperative neural networks to process complex sensorial data, Silva addressed one of the longstanding challenges in mobile robotics — enabling real-time obstacle detection and avoidance without prior environmental knowledge. This work garnered 9 citations and laid the groundwork for her subsequent research. Her 2003 paper, "Navigating mobile robots with a modular neural architecture," further refined these ideas, demonstrating the versatility and continued relevance of modular neural approaches in robotics. More recently, her contribution to "Progress in Artificial Intelligence" (2023) signals her sustained engagement with the evolving AI landscape. While her citation counts remain modest, Silva's work represents meaningful foundational contributions to intelligent robotic navigation and neural system design, offering valuable insights for researchers working at the intersection of AI and autonomous systems.