Global finite-time adaptive control for uncalibrated robot manipulator based on visual servoing

Area of Science:

• Robotics
• Control Systems
• Computer Vision

Background:

• Uncalibrated camera-robot systems face challenges with time-varying uncertainties in parameters.
• Existing methods often achieve asymptotic stability, which may not be sufficient for rapid convergence.

Purpose of the Study:

• To develop a finite-time convergence controller for uncalibrated camera-robot systems.
• To address uncertainties in camera parameters, robot dynamics, and feature depth.
• To enhance dynamic stability and ensure rapid convergence.

Main Methods:

• A novel finite-time stability (FTS) adaptive controller is proposed.
• FTS adaptive laws are designed to manage uncertainties in both robot and camera models.
• Finite-time stability analysis is performed using homogeneous theory and Lyapunov functions.

Main Results:

• The proposed controller achieves finite-time convergence for trajectory tracking errors.
• The method demonstrates improved dynamic stability compared to asymptotic approaches.
• Simulations validate the effectiveness of the finite-time adaptive control strategy.

Conclusions:

• The developed FTS adaptive control extends visual servoing from asymptotic to finite-time stability.
• This approach offers a robust solution for camera-robot systems with significant uncertainties.
• The findings pave the way for more precise and rapid robotic operations in dynamic environments.