Curvature Tracking of a Two-Segmented Soft Finger Using an Adaptive Sliding-Mode Controller

Abstract

The emergence of soft robotics in the last decade has brought about the exponential usage of elastomer bending robots in numerous fields of expertise from prosthetic hands to industrial grippers. While considerable attention has been drawn to static grasp, a substantial gap can be recognized in the development of soft grippers and anthropomorphic hands with the ability to manipulate objects dynamically, an ability that is referred to as in-hand object manipulation. In order to fill this gap, efficient and practical approaches should be investigated for the fabrication, modeling, and control of soft robots that are computationally efficient and capable of yielding repeatable results. Accordingly, in this article, qualified approaches for the dynamic modeling and control of a soft bending finger are introduced that can be efficiently implemented for planar in-hand manipulation applications in soft robotics. In this regard, a novel 3-D-printed mold is designed to cast a uniformly fabricated soft finger consisting of two independently actuated bending segments. After deriving the dynamic model of the soft finger and identifying its dynamic parameters, an adaptive sliding-mode controller is proposed to guarantee the convergence of the bending angles to desired trajectories under dynamic uncertainties and external disturbances. In the experimental validations, the root-mean-square errors of the proposed controller are 0.0323 and 0.0303 rad/m in free motion for each segment, while these numbers are 0.0328 and 0.0226 rad/m for constrained motion. For a comparative evaluation of the proposed controller, the results of the proportional–integral–differential controller are demonstrated under similar circumstances.