The realm of textiles spans clothing, households, healthcare, sports, and industrial
applications. The deformable nature of these objects poses unique challenges that prior …

Many assembled products contain parts that are not rigid, and there is a large variety of such
parts, which might be as different as cables, sheet metals, plastic covers, or foams. The …

Point clouds are a widely available and canonical data modality which convey the 3D
geometry of a scene. Despite significant progress in classification and segmentation from …

Combining gradient-based trajectory optimization with differentiable physics simulation is an
efficient technique for solving soft-body manipulation problems. Using a well-crafted …

One of the roadblocks for training generalist robotic models today is heterogeneity. Previous
robot learning methods often collect data to train with one specific embodiment for one task …

Automated industries lead to high quality production, lower manufacturing cost and better
utilization of human resources. Robotic manipulator arms have major role in the automation …

We study the problem of learning graph dynamics of deformable objects that generalizes to
unknown physical properties. Our key insight is to leverage a latent representation of elastic …

Realistic physics engines play a crucial role for learning to manipulate deformable objects
such as garments in simulation. By doing so, researchers can circumvent challenges such …

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 …

Tissue engineering, an interdisciplinary field, aims to restore, maintain, or enhance tissue
function by developing biological substitutes. To establish an optimal microenvironment …