Vision-Based Formation Control of Mobile Robots With FOV Constraints and Unknown Feature Depth
Zhiqiang Miao, Hang Zhong, Jie Lin, Yaonan Wang, Yanjie Chen, Rafael Fierro
Abstract
In this the problem of leader-following tracking control of wheeled mobile robots with implicit communication through onboard visual sensing is addressed. New image-based visual servoing (IBVS) control schemes are proposed to ensure prescribed performance and the field-of-view (FOV) constraints in the absence of the feature depth information. First, the error transformation with predefined performance specifications is introduced for handling the visibility constraints. Then, in the setting of control of the uncertain system with unknown control coefficients, a Nussbaum gain adaptive controller and a static nonlinear gain controller are proposed without the need of feature depth information. Finally, both numerical simulations and physical experiments are presented to demonstrate the applicability and performance of the proposed control schemes.