About

Andreas Ruf is a pioneer in the field of visual servoing and robotic control, with a focus on integrating computer vision and kinematics to enhance robot manipulation. His key research areas include model-based visual tracking, projective kinematics, and uncalibrated visual servoing, where he developed innovative approaches to guide robots using visual feedback without requiring precise calibration. Ruf's major contribution is the introduction of projective kinematics, a framework that simplifies visual servoing by operating directly in projective space, bypassing the need for traditional Euclidean calibration. His most cited work, "Visual tracking of an end-effector by adaptive kinematic prediction" (1997, 42 citations), demonstrates a robust method for tracking a moving tool in six degrees of freedom, enabling precise robot control in look-and-move mode. This work laid the foundation for his subsequent papers, including "Visual Servoing of Robot Manipulators Part I: Projective Kinematics" (1999, 28 citations), which further advanced the field. Ruf's research has had a lasting impact on robotics, particularly in applications requiring adaptive and vision-based guidance, making him a notable figure in the development of uncalibrated visual servoing techniques.

Research Focus

Key Achievements

3
H-Index
5
Papers
80
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Visual tracking of an end-effector by adaptive kinematic prediction
42 citations · 1997
📈 Most Prolific Year: 1999 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Centre Inria de l'Université Grenoble Alpes, Institut national de recherche en sciences et technologies du numérique

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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