Contour Moments Based Manipulation of Composite Rigid-Deformable Objects With Finite Time Model Estimation and Shape/Position Control

Abstract

The robotic manipulation of composite rigiddeformable objects (i.e., those with mixed nonhomogeneous stiffness properties) is a challenging problem with clear practical applications that, despite the recent progress in the field, it has not been sufficiently studied in the literature. To deal with this issue, in this article, we propose a new visual servoing method that has the capability to manipulate this broad class of objects (which varies from soft to rigid) with the same adaptive strategy. To quantify the object's infinite-dimensional configuration, our new approach computes a compact feedback vector of 2-D contour moments features. A sliding mode control scheme is then designed to simultaneously ensure the finite-time convergence of both the feedback shape error and the model estimation error. The stability of the proposed framework (including the boundedness of all the signals) is rigorously proved with Lyapunov theory. Detailed simulations and experiments are presented to validate the effectiveness of the proposed approach. To the best of the author's knowledge, this is the first time that contour moments along with finite-time control have been used to solve this difficult manipulation problem.

Model Predictive Manipulation of Compliant Objects with Multi-Objective Optimizer and Adversarial Network for Occlusion Compensation

“…Several representation methods have been proposed before, e.g., geometric features based on points, angles, curvatures, etc [7], [8]; However, due to their hard-coded nature, these methods can only be used to represent a single shaping action. Other geometric features computed from contours and centerlines [9]- [11] can represent soft object deformation in a more general way. Various data-driven approaches have also been proposed to represent shapes, e.g., using fast point feature histograms [12], bottleneck layers [13], [14], principal component analysis [15], etc.…”

“…In this paper, we consider a robot manipulator whose control inputs represent velocity commands (here, modelled as the differential changes ∆r). It is assumed that ∆r can be instantaneously executed without delay [11].…”

“…, p n ] ∈ R 3(n+1) as a compact feedback feature vector that represents the shape. We seek to minimize (11) to obtain a feature vector s that closely approximates c ≈ Bs. The solution to (11) is:…”

“…We seek to minimize (11) to obtain a feature vector s that closely approximates c ≈ Bs. The solution to (11) is:…”

Soft Robotic Mannequin: Design and Algorithm for Deformation Control

“…We aim to compute the optimized actuation for a soft mannequin utilizing vision feedback so that the mannequin deforms into a shape that provides the 'best' approximation for an input target shape. Vision feedback has been employed to build closed-loop control for manipulating deformable objects [19]- [21], however, it has not been developed to control freeform deformation as proposed.…”