Sanaa El Fkihi

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About

Sanaa El Fkihi is a researcher at the forefront of computer vision and robotics, with a focus on 3D digitization and autonomous navigation. Her work bridges the gap between theoretical sensor models and practical, real-world applications. A major contribution is her development of a non-model-based approach for complete digitization using terrestrial laser scanning (TLS) or mobile scanners. Her 2021 paper on this topic, which has garnered 7 citations, proposes an adaptive multi-objective view-planner that operates in unknown environments, guiding human operators to achieve full coverage of large, complex spaces—a significant step forward for automated scanning tasks. In the domain of visual perception, El Fkihi has also advanced the estimation of time-to-contact (TTC) for collision avoidance. Her 2013 paper, with 5 citations, introduces a novel gradient-based model for TTC estimation using paracatadioptric cameras, expanding this critical safety capability beyond standard perspective images to omnidirectional sensors. This work is particularly valuable for robotics applications requiring a wide field of view. Through these contributions, El Fkihi demonstrates a clear commitment to developing robust, sensor-adaptive algorithms that enhance the autonomy and efficiency of robotic systems in complex environments.