Cloth in the real world is often crumpled, self-occluded, or folded in on itself such that key
regions, such as corners, are not directly graspable, making manipulation difficult. We …

Manipulating cloth-like deformable objects (CDOs) is a long-standing problem in the
robotics community. CDOs are flexible (non-rigid) objects that do not show a detectable level …

Imitation learning has been applied to a range of robotic tasks, but can struggle when robots
encounter edge cases that are not represented in the training data (ie, distribution shift) …

Sequential multi-step cloth manipulation is a challenging problem in robotic manipulation,
requiring a robot to perceive the cloth state and plan a sequence of chained actions leading …

Cloud service providers provide over 50,000 distinct and dynamically changing set of cloud
server options. To help roboticists make cost-effective decisions, we present FogROS2 …

Fabric manipulation is a long-standing challenge in robotics due to the enormous state
space and complex dynamics. Learning approaches stand out as promising for this domain …

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 …

The manipulation of garments poses research challenges due to their deformable nature
and the extensive variability in shapes and sizes. Despite numerous attempts by …

Tracing–estimating the spatial state of–long deformable linear objects such as cables,
threads, hoses, or ropes, is useful for a broad range of tasks in homes, retail, factories …

The proficiency of robots in cloth manipulation is crucial for their potential widespread
deployment in household service contexts, with the task of unfolding cloth being particularly …