Papers
2
Total Citations
20
H-Index
2
About
Fabien Badeig is a researcher at the intersection of robotics, computer vision, and human-robot interaction, with a focus on enabling machines to perceive and respond to dynamic human environments. His key research areas include multi-person tracking, visually-guided robotic control, and the integration of digital twin technologies with artificial intelligence for industrial automation. Badeig’s most cited work, “Tracking a varying number of people with a visually-controlled robotic head” (2017, 18 citations), addresses a fundamental challenge in human-robot interaction: robustly tracking multiple individuals despite occlusions, appearance changes, and fluctuating crowd sizes, all while operating under the computational constraints of a physical robotic platform. This contribution is critical for safe and natural robot navigation in shared spaces. More recently, his work on “RoboTwin” (2023) explores the fusion of digital twin and AI domains to enhance robot control in Industry 4.0 settings, demonstrating a forward-looking approach to smart manufacturing. Badeig’s research is notable for its practical focus on real-world constraints, bridging theoretical tracking algorithms with the limitations of embedded hardware, and his ongoing work promises to advance both collaborative robotics and intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1Tracking a varying number of people with a visually-controlled robotic head18 citations · 2017
- 2