Papers
20
Total Citations
384
H-Index
10
About
Julien Moras is a robotics researcher whose work spans visual simultaneous localization and mapping (SLAM), 3D scene understanding, and autonomous navigation. He is perhaps best known for OV²SLAM (2021), a fully online and versatile visual SLAM system designed for real-time applications including augmented reality, robotics, and autonomous driving, which has garnered over 100 citations and stands as his most influential contribution to the field. His research consistently addresses the challenge of enabling robots to perceive, map, and navigate complex environments reliably — from turbid underwater settings, where his monocular visual odometry work (75 citations) tackled the unique degradations of aquatic conditions, to multi-robot collaborative systems capable of large-scale 3D surface reconstruction. Moras has also made significant contributions to semantic scene labeling through SnapNet-R (82 citations), integrating 3D-coherent observations for robust environmental understanding in robotic contexts. His earlier foundational work explored evidential grid mapping using Dempster-Shafer theory for dynamic environments, demonstrating a career-long interest in principled uncertainty management. Across his portfolio, Moras combines theoretical rigor with practical, real-time system design, making his research highly relevant to both academic roboticists and engineers developing next-generation autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2SnapNet-R: Consistent 3D Multi-view Semantic Labeling for Robotics82 citations · 2017
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- 8Distributed 3D TSDF Manifold Mapping for Multi-Robot Systems12 citations · 2019
- 9Evidential Grids Information Management In Dynamic Environments11 citations · 2014
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