Fabric manipulation has applications in folding blankets, handling patient clothing, and protecting items with covers. It is challenging for robots to perform fabric manipulation since fabrics have infinite-dimensional configuration spaces, complex dynamics, and may be in folded or crumpled configurations with severe self-occlusions. Prior work on robotic fabric manipulation relies either on heavily engineered setups or learning-based approaches that create and train on robot-fabric interaction data. In this paper, we propose GPT-Fabric for the canonical tasks of fabric smoothing and folding, where GPT directly outputs an action informing a robot where to grasp and pull a fabric. We perform extensive experiments in simulation to test GPT-Fabric against prior methods for smoothing and folding. GPT-Fabric matches the state-of-the-art in fabric smoothing, and also achieves comparable performance with most prior fabric folding methods tested, even without explicitly training on a fabric-specific dataset (i.e., zero-shot manipulation). Furthermore, we apply GPT-Fabric in physical experiments over 10 smoothing and 12 folding rollouts. Our results suggest that GPT-Fabric is a promising approach for high-precision fabric manipulation tasks
Automated Action Generation based on Action Field for Robotic Garment Smoothing and Alignment
JC STEM Lab of Robotics for Soft Materials（机器人软材料实验室）；Department of Electrical and Electronic Engineering（电气电子工程系）；Faculty of Engineering（工程学院）；The University of Hong Kong（香港大学）
SSFold: Learning to Fold Arbitrary Crumpled Cloth Using Graph Dynamics from Human Demonstration
Shanghai Research Institute for Intelligent Autonomous Systems（上海智能自主系统研究院）；National Key Laboratory of Autonomous Intelligent Unmanned Systems (Tongji University)（自主智能无人系统国家重点实验室（同济大学））；Frontiers Science Center for Intelligent Autonomous Systems（智能自主系统前沿科学中心）；College of Electronics and Information Engineering, Tongji University（同济大学电子信息工程学院）
Robot Deformable Object Manipulation via NMPC-generated Demonstrations in Deep Reinforcement Learning
Hubei Key Laboratory of Brain-inspired Intelligent Systems and the Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（湖北脑启发智能系统重点实验室和图像处理与智能控制重点实验室，人工智能与自动化学院，华中科技大学）
