Addressing target loss and actuator saturation in visual servoing of multirotors: A nonrecursive augmented dynamics control approach

Abstract

Traditional position and image-based visual servoing techniques often pose challenges in terms of target loss and actuator saturation. These challenges arise due to the requirement of calculating inverse Jacobians to determine robot motions and the susceptibility of these methods to image noise. To address the aforementioned challenges, this article presents a nonrecursive augmented dynamics control (NRADC) that establishes a direct correlation between variations in image pixels and the thrust and torque commands of a multirotor. By incorporating pixel variations into the dynamics of the multirotor, this approach enables the utilization of state constraints to address the issue of target loss. In addition, the correlation between image pixels and control commands allows for the integration of image noise with system uncertainties. Consequently, a single controller can be designed to simultaneously handle both aspects while considering input constraints, effectively addressing the problem of actuator saturation. Notably, unlike conventional control approaches that handle input and state constraints, the proposed NRADC approach is nonrecursive, making it well suited for implementation on systems with limited on-board computational resources, such as multirotors. The effectiveness of the proposed method is demonstrated through experimental validations, including a performance comparison with a nonrecursive controller from recent literature.

Keywords

• nonrecursive control
• augmented dynamics
• visual servoing
• multirotor
• state constraints
• input constraints
• target loss
• actuator saturation