Eduardo Ochoa
Papers
4
Total Citations
20
H-Index
3
About
Eduardo Ochoa is a marine robotics researcher whose work focuses on making underwater exploration safer, more accessible, and more data-driven. His primary research areas include collision detection and avoidance, omnidirectional vision systems, and simulation environments for autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). Ochoa’s major contribution is the development of real-time collision avoidance using omnidirectional cameras, which allows ROVs to navigate hazardous seabed environments with minimal human intervention. This innovation is especially critical for enabling untrained scientists to safely pilot ROVs during marine habitat studies, reducing the risk of costly damage to both equipment and ecosystems. His most cited work, “Collision Detection and Avoidance for Underwater Vehicles Using Omnidirectional Vision” (2022), has garnered 9 citations and underscores the growing demand for safer autonomous operations. Ochoa also co-created Stonefish, an open-source simulator designed to support machine learning research in marine robotics, bridging the gap between costly field trials and reproducible, controlled testing. With over 20 total citations across his publications, Ochoa is helping to democratize underwater science by making advanced robotic tools more robust and user-friendly.
Research Focus
Key Achievements
Top Papers
- 1
- 2Stonefish: Supporting Machine Learning Research in Marine Robotics5 citations · 2025
- 3
- 4Stonefish: Supporting Machine Learning Research in Marine Robotics3 citations · 2025