Miquel Massot‐Campos
Universitat de les Illes Balears, Demos, University of Southampton
Papers
9
Total Citations
171
H-Index
7
About
Miquel Massot‐Campos is a leading researcher in autonomous underwater robotics, with a primary focus on visual sensing, navigation, and environmental monitoring. His work bridges the gap between computer vision, robotics, and marine ecology, enabling autonomous underwater vehicles (AUVs) to explore, map, and assess fragile underwater ecosystems. He is best known for developing visual sensing frameworks that allow lightweight AUVs to perform autonomous exploration and intervention tasks, as detailed in his most-cited work (62 citations). A major contribution is his pioneering use of deep learning and AUVs for the detection, mapping, and quantification of *Posidonia oceanica*, a critical Mediterranean seagrass that serves as an indicator of coastal water quality. His research also advances underwater 3D reconstruction through structured light and stereo vision, and he has developed innovative solutions for inertial sensor self-calibration in micro-AUVs. With over 170 citations across his top papers, Massot‐Campos has demonstrated significant impact in both robotic perception and marine conservation. His recent work on leveraging metadata in representation learning and virtual reality subsea exploration (ARSEA) further highlights his commitment to making underwater data collection more efficient, immersive, and actionable for scientists and engineers alike.
Research Focus
Key Achievements
Top Papers
- 1Visual sensing for autonomous underwater exploration and intervention tasks62 citations · 2014
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- 4Structured light and stereo vision for underwater 3D reconstruction19 citations · 2015
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- 6Laser Stripe Bathymetry using Particle Filter SLAM10 citations · 2019
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- 9ARSEA: A Virtual Reality Subsea Exploration Assistant5 citations · 2018