Miguel García-Silvente
Universidad de Granada, Polytechnic University of Puerto Rico
Papers
12
Total Citations
149
H-Index
7
About
Miguel García-Silvente’s research lies at the intersection of mobile robotics, computer vision, and intelligent control, with a core focus on enabling robots to perceive and interact with humans in dynamic environments. His major contributions span two decades, beginning with pioneering work on fuzzy visual systems for robot navigation—such as his 2006 paper on detecting doors using a genetic visual fuzzy system (31 citations) and his 2008 study on automatic tuning of fuzzy systems via evolutionary algorithms (26 citations). He has been instrumental in advancing people detection and tracking, combining stereo vision, laser rangefinders, and deep learning to create robust systems for human-robot interaction. Notable achievements include his 2005 work on people detection through stereo vision (20 citations) and his 2013 leg detection method using supervised learning and particle filtering (15 citations). More recently, García-Silvente has integrated deep learning with 2D laser data, as seen in his 2019 paper (8 citations) and 2022 follow-up (7 citations), demonstrating sustained innovation. His multi-agent system architectures for navigation (2005, 15 citations) further highlight his holistic approach to robotics. With over 150 total citations across his top ten papers, García-Silvente’s work has shaped how mobile robots detect, track, and interact with people in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1Detection of doors using a genetic visual fuzzy system for mobile robots31 citations · 2006
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- 8Detecting and tracking using 2D laser range finders and deep learning7 citations · 2022
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