Samuel-Felipe Baltanas

Instituto de Investigación Biomédica de Málaga

Papers

Total Citations

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About

Samuel-Felipe Baltanas is a researcher at the intersection of robotics, computer vision, and engineering education. His primary contributions lie in developing robust face recognition systems for assistive and mobile robots, addressing critical challenges in Human-Robot Interaction (HRI). He has notably tackled the "head pose variation problem," a major obstacle in deploying reliable face recognition in dynamic, real-world environments where users are not always facing the camera directly. His work on a dedicated face recognition system for assistive robots (7 citations) underscores the importance of non-intrusive, personalized service in fields like education and healthcare. Beyond vision, Baltanas is a pioneer in modern pedagogical methods, authoring a highly influential case study on using Jupyter Notebooks in undergraduate mobile robotics courses (12 citations). This work highlights how interactive, code-driven textbooks can bridge the gap between theoretical concepts and practical application, making complex robotics topics more accessible. His research demonstrates a clear commitment to both advancing the technical capabilities of service robots and improving how the next generation of engineers learns to build them.