Vision-based range estimation via Immersion and Invariance for robot formation control
Fabio Morbidi, Gian Luca Mariottini, Domenico Prattichizzo · 2008
The paper introduces a new vision-based range estimator based upon the Immersion and Invariance (I&I) methodology, for leader-follower formation control. The proposed reduced-order nonlinear observer achieves global exponential convergence of the observation error to zero and it is extremely simple to implement and to tune. A Lyapunov analysis is provided to show the stability of the closed-loop system arising from the combination of the range estimator and an input-state feedback controller. Simulation experiments illustrate the theory and show the effectiveness of the proposed design.