Papers
3
Total Citations
73
H-Index
2
About
David Souto is a leading researcher in autonomous robotic navigation and control, with a primary focus on path following strategies for marine, ground, and aerial vehicles. His major contributions include comprehensive reviews and novel control frameworks that unify path following error dynamics across diverse vehicle classes, particularly emphasizing 2D motion and real-world experimental validation. His most cited work, a 2022 review on path following control strategies, has accumulated 71 citations, underscoring its influence in the field. Souto has also advanced underwater navigation through multi-sensor fusion, developing a particle filter approach that integrates bathymetric data from multibeam echosounders with prior digital elevation maps for robust geophysical localization of autonomous underwater vehicles. This work addresses critical challenges in GPS-denied environments, enabling precise navigation in deep-sea operations. Souto’s research bridges theoretical control design with practical simulation and experimental testing, making his contributions highly relevant for students and engineers developing next-generation autonomous systems. His achievements highlight a commitment to solving real-world navigation problems, from surface vessels to underwater explorers.
Research Focus
Key Achievements
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