We explore a novel method to perceive and manipulate 3D articulated objects that
generalizes to enable a robot to articulate unseen classes of objects. We propose a vision …

We study the problem of learning to perform multistage robotic manipulation tasks, with
applications to cable routing, where the robot must route a cable through a series of clips …

We present RoboGen, a generative robotic agent that automatically learns diverse robotic
skills at scale via generative simulation. RoboGen leverages the latest advancements in …

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 …

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 …

Folding garments reliably and efficiently is a long standing challenge in robotic manipulation
due to the complex dynamics and high dimensional configuration space of garments. An …

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

This paper introduces DextAIRity, an approach to manipulate deformable objects using
active airflow. In contrast to conventional contact-based quasi-static manipulations …

Self-occlusion is challenging for cloth manipulation, as it makes it difficult to estimate the full
state of the cloth. Ideally, a robot trying to unfold a crumpled or folded cloth should be able to …

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 …