Strategy for folding clothing on the basis of deformable models

Abstract

In this study, a strategy is given for automatically reshaping an item of clothing from an arbitrary shape into a fixed shape by using its deformable model. The strategy consists of three stages that correspond to the clothing state: unknown (before recognition), unknown to known (recognition), and known (after recognition). In the first stage, a clothing item that is initially placed in an arbitrary shape is picked up and observed after some recognition-aid actions. In the second stage, the clothing state is recognized by matching the deformable clothing model to the observed 3D data [1]. In the third stage, a proper sequence of grasps toward the goal state is selected according to the clothing state. As an instance of this strategy, a folding task was implemented in a humanoid robot. Experimental results using pullovers show that the folding task can be achieved with a small number of grasping steps.