One Fling to Goal: Environment-aware Dynamics for Goal-conditioned Fabric Flinging

TL;DR

This paper introduces a real-time, environment-aware graph-based dynamics model for goal-conditioned fabric manipulation, enabling fast and accurate fabric positioning across diverse scenarios with zero-shot transfer to real robots.

Contribution

The authors propose a novel graph-based dynamics model with environmental awareness for fabric manipulation, achieving fast, accurate, and transferable goal-conditioned control.

Findings

Achieves less than 3 seconds per goal in fabric manipulation tasks.

Average error of 13.2mm in complex scenarios.

Successfully transfers to real-world robotic systems in zero-shot.

Abstract

Fabric manipulation dynamically is commonly seen in manufacturing and domestic settings. While dynamically manipulating a fabric piece to reach a target state is highly efficient, this task presents considerable challenges due to the varying properties of different fabrics, complex dynamics when interacting with environments, and meeting required goal conditions. To address these challenges, we present \textit{One Fling to Goal}, an algorithm capable of handling fabric pieces with diverse shapes and physical properties across various scenarios. Our method learns a graph-based dynamics model equipped with environmental awareness. With this dynamics model, we devise a real-time controller to enable high-speed fabric manipulation in one attempt, requiring less than 3 seconds to finish the goal-conditioned task. We experimentally validate our method on a goal-conditioned manipulation task in five diverse scenarios. Our method significantly improves this goal-conditioned task, achieving an average error of 13.2mm in complex scenarios. Our method can be seamlessly transferred to real-world robotic systems and generalized to unseen scenarios in a zero-shot manner.