Papers
11
Total Citations
133
H-Index
5
About
Nicolas Ragot is a leading researcher at the intersection of assistive robotics, computer vision, and human-machine collaboration. His work centers on developing intelligent robotic systems that enhance human capabilities, with a particular focus on assistive technologies for individuals with disabilities and flexible manufacturing systems. Ragot’s most impactful contribution is his 2023 systematic literature review on human-machine collaboration through digital twins and extended reality, which has garnered 38 citations and established a foundational framework for the field. He is also recognized for his benchmark of visual SLAM algorithms (ORB-SLAM2 vs RTAB-Map, 30 citations), which provides critical guidance for robotic navigation systems. A key achievement is his leadership in the EU’s Interreg ADAPT project, where he co-designed modular robotic assistive technologies for smart wheelchairs (30 citations), directly improving users’ quality of life. Ragot has also pioneered the concept of “Augmented Perception” for resilient manufacturing, integrating digital twins with robotic agents. His work on synthetic datasets for industrial object pose estimation and calibration of panoramic stereovision sensors further demonstrates his versatility. With a career spanning from early work on NAO humanoid robots to cutting-edge digital twin applications, Ragot’s research consistently bridges theoretical advances with real-world impact in assistive and industrial robotics.
Research Focus
Key Achievements
Top Papers
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- 2Benchmark of Visual SLAM Algorithms: ORB-SLAM2 vs RTAB-Map30 citations · 2019
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- 10ROS-based Autonomous Navigation Wheelchair using Omnidirectional Sensor2 citations · 2016