BACKGROUND Humans have a fantastic ability to manipulate objects of various shapes,
sizes, and materials and can control the objects' position in confined spaces with the …

This paper aims to provide a comprehensive survey of recent advancements in modelling
and autonomous manipulation of non-rigid objects. It first summarizes the recent advances …

We have seen much recent progress in rigid object manipulation, but interaction with
deformable objects has notably lagged behind. Due to the large configuration space of …

Denoising diffusion probabilistic models that were initially proposed for realistic image
generation have recently shown success in various perception tasks (eg, object detection …

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 …

In this paper we present a Deep Reinforcement Learning approach to solve dynamic cloth
manipulation tasks. Differing from the case of rigid objects, we stress that the followed …

Human pose estimation aims at localizing human anatomical keypoints or body parts in the
input data (eg, images, videos, or signals). It forms a crucial component in enabling …

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

Temporal modeling is crucial for multi-frame human pose estimation. Most existing methods
directly employ optical flow or deformable convolution to predict full-spectrum motion fields …

Autonomous robots have the potential to serve as versatile caregivers that improve quality of
life for millions of people worldwide. Yet, conducting research in this area presents …