Marios Xanthidis
Papers
12
Total Citations
1,311
H-Index
7
About
Marios Xanthidis is a robotics researcher specializing in autonomous underwater vehicles, state estimation, and motion planning for complex, unstructured environments. His work sits at the intersection of perception, localization, and multi-robot coordination, with a particular focus on pushing autonomy into some of robotics' most challenging domains — underwater settings where conventional algorithms frequently struggle. Xanthidis gained significant recognition for his rigorous experimental comparisons of visual and visual-inertial state estimation algorithms, with his 2019 IROS-affiliated work accumulating over 1,079 citations and a companion study reaching 101 citations — establishing him as an important voice in benchmarking perception systems beyond standard indoor and urban datasets. His 2017 vision-based state estimation comparison (73 citations) further cemented this contribution. Beyond evaluation, Xanthidis has made meaningful advances in underwater motion planning, multi-robot exploration of submerged structures, and deep learning-based relative localization for AUV teams. More recently, his research has expanded into aquaculture automation, recognizing the growing industrial need for reliable underwater autonomy. Across his career, his work reflects a consistent drive to bridge the gap between state-of-the-art algorithms and real-world deployment in environments where robustness truly matters.
Research Focus
Key Achievements
Top Papers
- 12019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)1,079 citations · 2019
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- 5Active localization with dynamic obstacles10 citations · 2016
- 6Multi-Robot Exploration of Underwater Structures8 citations · 2022
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