About

Patrick Gros is a leading researcher in computer vision and robotics, specializing in visual servoing, object modeling, and landmark recognition. His work addresses fundamental challenges in enabling robots to perceive and interact with their environments autonomously. A key contribution is his research on image-based visual servoing under large displacements, where he tackled the critical problem of trajectory failure during large robot motions—a deficiency that limited practical deployment. His 2003 paper on this topic, with 18 citations, proposed interpolation methods to ensure physically valid trajectories, advancing the reliability of visual control systems. Gros also made foundational contributions to automatic object modeling, developing frameworks for matching and clustering multiple images to generate 3D polyhedral models without manual intervention. His 1995 paper (16 citations) and earlier 1993 work laid groundwork for robot recognition, localization, and grasping. More recently, his 2018 study on visual learning for landmark recognition (9 citations) addresses mobile robot positioning and mapping, shifting from rigid geometric models to learned representations for unknown environments. With a career spanning decades, Gros’s research bridges theoretical advances and practical robotics, influencing autonomous navigation and object manipulation.

Research Focus

Key Achievements

4
H-Index
4
Papers
47
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Images interpolation for image-based control under large displacement
18 citations · 2003
📈 Most Prolific Year: 2003 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Institut de Recherche en Informatique et Systèmes Aléatoires, Institut national de recherche en sciences et technologies du numérique, Carnegie Mellon University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago