Visual Tracking Control of Deformable Objects With a FAT-Based Controller

Automatic manipulation of deformable objects is a challenging problem. Improper operations, such as excessive stretching and collision, are easy to cause damages to the deformable objects. Thus, not only the final configuration but also the trajectory of the deformation is supposed to be controlled during the process of interaction. In this article, a method to control the trajectory of the deformation in the unknown environment is proposed. We design an adaptive dynamic controller that adaptively estimates the deformation Jacobian matrix (DJM) online based on function approximation techniques (FAT), which approximates nonlinear functions with an arbitrary small error, avoiding modeling for compliant objects. Besides, we introduce a virtual force to improve the manipulability of the method. The stability of the proposed adaptive algorithm and the boundedness of internal signals are proved by Lyapunov theory whenever the approximation error is nonnegligible or negligible. Experiment results validate the efficiency of the algorithm proposed.

Automated summary

This article proposes a method to control the trajectory of deformation in an unknown environment. An adaptive dynamic controller is designed to estimate the deformation Jacobian matrix based on function approximation techniques, and a virtual force is introduced to improve manipulability.