Marwen Jabeur

Papers

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About

Marwen Jabeur is a researcher specializing in robotics and computer vision, with a particular focus on visual servoing—the use of visual feedback to control robotic systems. His most-cited work, "Image-Based Visual Servoing With Unknown Point Feature Correspondence" (2016, 29 citations), introduces a novel approach that simultaneously addresses the challenge of feature correspondence and control in image-based visual servoing. By employing a finite-time optimal control framework, Jabeur’s method eliminates the need for explicit feature matching, enabling robots to operate effectively even when visual correspondences are unknown or ambiguous. This contribution is significant for real-world applications where lighting, occlusions, or rapid motion can disrupt traditional correspondence algorithms. Jabeur’s work has been recognized for advancing the robustness and autonomy of robotic systems, particularly in unstructured environments. His research bridges theoretical control theory and practical computer vision, offering solutions that enhance the reliability of vision-guided robots. With a growing citation count, Jabeur continues to influence the fields of robotics and automation, making his work essential reading for students and researchers interested in intelligent, visually guided systems.