Model-Free Large-Scale Cloth Spreading With Mobile Manipulation: Initial Feasibility Study

TL;DR

This study demonstrates the feasibility of using a single-arm mobile manipulator with a model-free, vision-based control scheme and Behavior Trees to spread large-scale cloth, addressing reachability and control challenges.

Contribution

It introduces a novel framework combining a mobile manipulator, model-free control, and Behavior Trees for large-scale cloth spreading tasks.

Findings

Successful large-scale cloth spreading with a mobile manipulator

Validation of model-free, vision-based manipulation control

Demonstrated task feasibility in various conditions

Abstract

Cloth manipulation is common in domestic and service tasks, and most studies use fixed-base manipulators to manipulate objects whose sizes are relatively small with respect to the manipulators' workspace, such as towels, shirts, and rags. In contrast, manipulation of large-scale cloth, such as bed making and tablecloth spreading, poses additional challenges of reachability and manipulation control. To address them, this paper presents a novel framework to spread large-scale cloth, with a single-arm mobile manipulator that can solve the reachability issue, for an initial feasibility study. On the manipulation control side, without modeling highly deformable cloth, a vision-based manipulation control scheme is applied and based on an online-update Jacobian matrix mapping from selected feature points to the end-effector motion. To coordinate the control of the manipulator and mobile platform, Behavior Trees (BTs) are used because of their modularity. Finally, experiments are conducted, including validation of the model-free manipulation control for cloth spreading in different conditions and the large-scale cloth spreading framework. The experimental results demonstrate the large-scale cloth spreading task feasibility with a single-arm mobile manipulator and the model-free deformation controller.