Zakariae Machkour
Papers
2
Total Citations
37
H-Index
2
About
Zakariae Machkour is a rising researcher at the intersection of robotics, computer vision, and deep learning, with a primary focus on developing intelligent perception and navigation systems for autonomous ground robots. His work bridges classical control theory with modern deep learning approaches, particularly in the domain of visual servoing—the use of visual feedback to control robot motion. His most cited work, a comprehensive 2021 survey on classical and deep learning-based visual servoing systems (29 citations), has become a valuable resource for researchers navigating this rapidly evolving field, establishing him as a thoughtful synthesizer of state-of-the-art techniques. In a notable 2023 contribution, Machkour proposed a monocular-based navigation system for autonomous ground robots that leverages multiple deep learning models to achieve human-like perception using only a single camera, eliminating the need for expensive lidar or radar sensors. This work demonstrates his commitment to practical, cost-effective solutions for real-world robotics. With a growing citation footprint and a focus on making autonomous navigation more accessible, Machkour is an emerging voice in the robotics community, particularly for those interested in the synergy between deep learning and classical control for visual perception.
Research Focus
Key Achievements
Top Papers
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