Papers
6
Total Citations
40
H-Index
3
About
Cyril Joly is a robotics and autonomous systems researcher whose work spans mobile robot localization, sensor fusion, and 3D scene understanding. He is perhaps best known for his contributions to indoor topological localization, where he pioneered novel frameworks that merge visual and Wi-Fi data without requiring prior knowledge of building layouts or access point positions. His FABMAP-based early-fusion approach, introduced in 2017 and extended in 2020, addresses challenging problems such as global localization and the kidnapped robot problem, earning a combined 25 citations across both studies. Earlier in his career, Joly tackled foundational challenges in Simultaneous Localization and Mapping (SLAM), contributing a bearing-only approach using minimal inverse depth parametrization applied to omnidirectional camera systems, work conducted at INRIA Sophia Antipolis. His research has also extended into practical autonomous driving applications, including LiDAR-based 3D reconstruction for driver assistance in rough, non-urban environments and, more recently, real-time LiDAR semantic segmentation for autonomous platforms. Across these diverse contributions, Joly demonstrates a consistent focus on making robotic perception robust, computationally efficient, and deployable in real-world conditions — qualities that make his work highly relevant to students and practitioners in robotics and autonomous systems alike.
Research Focus
Key Achievements
Top Papers
- 1Topological localization using Wi-Fi and vision merged into FABMAP framework14 citations · 2017
- 2Vision and Wi-Fi fusion in probabilistic appearance-based localization11 citations · 2020
- 3
- 4Nonurban Driver Assistance with 2D Tilting Laser Reconstruction3 citations · 2017
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