Papers

6

Total Citations

155

H-Index

5

About

Andouglas Silva is a Brazilian robotics and autonomous systems researcher whose work centers on autonomous marine vehicles, path planning, and environmental monitoring. Best known for his pioneering contributions to robotic sailboat technology, Silva has spent over a decade advancing the design, control, and intelligence of wind-propelled autonomous vessels capable of long-endurance ocean missions. His most cited work, "High-Level Path Planning for an Autonomous Sailboat Robot Using Q-Learning" (2020, 70 citations), demonstrated how reinforcement learning could elegantly solve the complex navigational challenges unique to sail-driven robots. Earlier foundational contributions, including the N-BOAT project (2013) and a comprehensive control system architecture (2016, 34 citations), established robust frameworks that the broader autonomous maritime community has built upon. Silva also bridges robotics with environmental science, developing real-time embedded systems for water quality monitoring deployed aboard robotic sailboats, reflecting a commitment to socially impactful applications. His more recent exploration of holography-based microparticle detection in water samples signals an exciting expansion into optical sensing and environmental diagnostics. With over 150 cumulative citations, Silva's research represents a distinctive and growing intersection of autonomous navigation, machine learning, and ecological stewardship.

Research Focus

Key Achievements

5
H-Index
6
Papers
155
Total Citations
26
Avg Citations/Paper
🏆 Most Cited Paper
High-Level Path Planning for an Autonomous Sailboat Robot Using Q-Learning
70 citations · 2020
📈 Most Prolific Year: 2016 (2 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Instituto Federal do Rio Grande do Norte, Universidade Federal do Rio Grande do Norte

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago