Papers
1
Total Citations
34
H-Index
1
About
Erika Assis is a leading researcher in mobile robotics, specializing in autonomous navigation, sensor fusion, and machine learning for localization systems. Her work addresses a critical challenge in robotics: enabling robots to accurately determine their position and navigate in unknown environments. Her most-cited paper, "Localization System for Autonomous Mobile Robots Using Machine Learning Methods and Omnidirectional Sonar" (2018, 34 citations), demonstrates her innovative approach to combining signal processing techniques with machine learning to enhance robot autonomy. This research is foundational for applications ranging from industrial automation to search-and-rescue operations. Assis’s contributions have practical significance, as they improve the reliability and efficiency of robotic systems operating without GPS or pre-mapped environments. Her work is widely recognized, with her top-cited paper serving as a key reference for researchers exploring sonar-based localization and intelligent sensor integration. By bridging machine learning and robotics, Assis continues to advance the field, offering solutions that make autonomous mobile robots more adaptable and robust in real-world settings.
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