Optimal Cosserat-based deformation control for robotic manipulation of linear objects

TL;DR

This paper introduces a novel closed-loop shape control method for deformable linear objects that combines Cosserat physics-based modeling with vision feedback, enabling real-time, accurate, and robust deformation control in robotic manipulation.

Contribution

The paper presents a new 3D shape control approach integrating Cosserat models with vision feedback for improved real-time deformation control of linear objects.

Findings

Effective real-time shape correction demonstrated in robotic experiments.

Enhanced robustness to elastic parameter estimation errors.

Combines physics-based modeling with visual feedback for improved accuracy.

Abstract

The robotic shape control of deformable linear objects has garnered increasing interest within the robotics community. Despite recent progress, the majority of shape control approaches can be classified into two main groups: open-loop control, which relies on physically realistic models to represent the object, and closed-loop control, which employs less precise models alongside visual data to compute commands. In this work, we present a novel 3D shape control approach that includes the physically realistic Cosserat model into a closed-loop control framework, using vision feedback to rectify errors in real-time. This approach capitalizes on the advantages of both groups: the realism and precision provided by physics-based models, and the rapid computation, therefore enabling real-time correction of model errors, and robustness to elastic parameter estimation inherent in vision-based approaches. This is achieved by computing a deformation Jacobian derived from both the Cosserat model and visual data. To demonstrate the effectiveness of the method, we conduct a series of shape control experiments where robots are tasked with deforming linear objects towards a desired shape.