Research and application of reinforcement learning in robotics for contact-rich manipulation
tasks have exploded in recent years. Its ability to cope with unstructured environments and …

The motivation behind our work is to review and analyze the most relevant studies on deep
reinforcement learning-based object manipulation. Various studies are examined through a …

Rearranging and manipulating deformable objects such as cables, fabrics, and bags is a
long-standing challenge in robotic manipulation. The complex dynamics and high …

High-velocity dynamic actions (eg, fling or throw) play a crucial role in our everyday
interaction with deformable objects by improving our efficiency and effectively expanding our …

This paper tackles the task of goal-conditioned dynamic manipulation of deformable objects.
This task is highly challenging due to its complex dynamics (introduced by object …

We address the problem of goal-directed cloth manipulation, a challenging task due to the
deformability of cloth. Our insight is that optical flow, a technique normally used for motion …

Sequential pulling policies to flatten and smooth fabrics have applications from surgery to
manufacturing to home tasks such as bed making and folding clothes. Due to the complexity …

Garment folding is a ubiquitous domestic task that is difficult to automate due to the highly
deformable nature of fabrics. In this article, we propose a novel method of learning from …

Robotic fabric manipulation has applications in home robotics, textiles, senior care and
surgery. Existing fabric manipulation techniques, however, are designed for specific tasks …

Understanding and manipulating deformable objects (eg, ropes and fabrics) is an essential
yet challenging task with broad applications. Difficulties come from complex states and …