Miguel Vaz
Papers
2
Total Citations
13
H-Index
2
About
Miguel Vaz is a researcher in mobile robotics, with a primary focus on real-time localization and perception in unstructured environments. His work addresses a critical challenge in domestic and service robotics: achieving reliable absolute localization without relying on structured features like vertical walls. His most cited contributions center on a ground-plane based localization method using depth cameras, which enables robots to determine their position in real-world scenarios where traditional approaches fail. This technique, detailed in his 2014 and 2015 papers, has garnered a combined 13 citations, reflecting its practical relevance for autonomous navigation in cluttered, human-centric spaces. By leveraging the ground plane as a stable reference, Vaz’s work improves the generality and robustness of mobile robot localization, moving beyond laboratory conditions to real domestic environments. His research is particularly valuable for the development of assistive and household robots, where adaptability and real-time performance are essential. Vaz’s contributions underscore a commitment to making autonomous systems more capable in the complex, unpredictable settings of everyday life.
Research Focus
Key Achievements
Top Papers
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