Learning to Put On a Knit Cap in a Head-Centric Policy Space

Robotic manipulation of such highly deformable objects as clothes is a challenging problem. Robot-assisted dressing adds even more complexity as the garment motions must be aligned with a human body under conditions of strong and variable occlusion. As a step toward solutions for the general task, we consider the example of a dual-arm robot with attached anthropomorphic hands that learns to put a knit cap on a styrofoam head. Our approach avoids modeling the details of the garment and its deformations. Instead, we demonstrate that a head-centric policy parameterization, combined with a suitable objective function for determining the right amount of contact between the cap and the head, enables a direct policy search algorithm to find successful trajectories for this task. We also show how a toy problem that mirrors some of the task constraints can be used to efficiently structure hyperparameter search. Additionally, we suggest a point cloud based algorithm for modeling the head as an ellipsoid which is required for defining the policy space.