Adaptive event-triggered control for uncalibrated visual servoing of robot manipulators

In the study, an adaptive event-triggered control strategy is proposed for image-based visual servoing of eye-to-hand robot manipulators, where the camera used does not need to be calibrated, and the dynamics behavior of manipulator is considered in design and analysis. To address the uncertainty in camera parameters and the nonlinearity in robot dynamics, and accommodate the errors between the real-time control signals and the piecewise-constant event-triggered control signals, a new and novel robust adaptive estimation approach is developed, and well fused with visual feedback control design so that the boundedness of all closed-loop signals, and the asymptotic convergence of image error towards zero are established simultaneously. Besides rigorous proof in theory, the obtained results are also confirmed by comparative simulation tests. (c) 2023 The Franklin Institute. Published by Elsevier Inc. All rights reserved.

Automated summary

An adaptive event-triggered control strategy is proposed for image-based visual servoing of eye-to-hand robot manipulators in which an uncalibrated camera and the dynamics behavior of the manipulator are considered. A robust adaptive estimation approach is developed to address the uncertainty in camera parameters and the nonlinearity in robot dynamics, achieving boundedness of closed-loop signals and asymptotic convergence of image error to zero. Comparative simulation tests confirm the obtained results.