Xavier Dutoit
Papers
5
Total Citations
94
H-Index
4
About
Xavier Dutoit’s research lies at the intersection of robotics, computer vision, and intelligent control, with a primary focus on enabling robust human-robot interaction through visual tracking. His major contributions center on developing advanced visual tracking control systems for mobile robots, particularly those modeled as unicycle platforms with tilt cameras. Dutoit pioneered the use of a dual-Jacobian visual interaction model to decouple and control the complex dynamics of camera and robot motion, allowing for precise tracking of human faces and targets even under external uncertainties. To enhance system robustness, he integrated self-tuning Kalman filters with echo state networks (a form of reservoir computing) for visual state estimation, enabling the system to estimate target status and image velocity without prior knowledge of the target. His work on event detection and localization using reservoir computing further advanced mobile robot navigation. With his most-cited papers accumulating 27 and 26 citations respectively, Dutoit’s research has provided foundational techniques for reliable, real-time visual tracking in human-robot interaction scenarios, making him a notable figure in the field of intelligent robotic control.
Research Focus
Key Achievements
Top Papers
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