Papers

13

Total Citations

137

H-Index

6

About

Matheus M. dos Santos is a researcher specializing in autonomous underwater robotics, with a particular focus on acoustic perception, place recognition, and robot localization in challenging aquatic environments. His work addresses one of the most pressing obstacles in underwater autonomy: enabling robots to navigate reliably without GPS, in turbid, acoustically complex conditions where traditional sensors fail. Santos has made significant contributions to the development of topological descriptors for forward-looking sonar (FLS) images, pioneering methods that allow autonomous underwater vehicles (AUVs) to recognize previously visited locations using acoustic imagery alone. His most cited work, "Underwater Place Recognition Using Forward-Looking Sonar Images" (2018, 40 citations), established a foundational topological framework for sonar-based navigation. He further advanced this field through deep learning approaches, including triplet network architectures for acoustic image retrieval and cross-domain matching between aerial and underwater sensor modalities. A recurring theme across his research is sensor fusion — combining sonar, aerial imagery, and neural networks to achieve robust localization under unmodeled noise and environmental uncertainty. His work on 3D underwater reconstruction using MSIS sonar further demonstrates his broad contributions to robotic perception. With over 120 cumulative citations, Santos represents a growing voice in underwater robotic autonomy research.

Research Focus

Key Achievements

6
H-Index
13
Papers
137
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Underwater place recognition using forward‐looking sonar images: A topological approach
40 citations · 2018
📈 Most Prolific Year: 2018 (4 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Universidade Federal do Rio Grande, Robotics Research (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago