Antoine Manzanera
Papers
7
Total Citations
34
H-Index
5
About
Antoine Manzanera is a leading researcher at the intersection of aerial robotics, computer vision, and evolutionary computation. His work focuses on developing autonomous systems that can perceive and navigate their environments without human intervention. A pioneer in the use of genetic programming for robotics, Manzanera demonstrated that evolutionary algorithms could automatically design vision-based obstacle avoidance controllers, achieving over 5 citations per paper for his foundational work on evolving visual controllers and two-phase genetic programming systems. His research on the generalization performance of evolved vision controllers established critical benchmarks for autonomous navigation. More recently, Manzanera has become a driving force in robotics education, creating DroMOOC, a massive open online course on drones and aerial multi-robot systems that has garnered 9 citations and reached an international audience. He has also advanced the field by integrating experimental datasets and simulation codes into educational platforms, making complex aerial robotics concepts accessible to students worldwide. His work on ground-plane classification for robot navigation, which combines multiple visual cues for learning-based systems, further showcases his commitment to building robust, intelligent robots that can operate in real-world environments.
Research Focus
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