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 …

Policy learning in robot-assisted surgery (RAS) lacks data efficient and versatile methods
that exhibit the desired motion quality for delicate surgical interventions. To this end, we …

In this article, we propose a general unified tracking-servoing approach for controlling the
shape of elastic deformable objects using robotic arms. Our approach works by forming a …

Manipulating deformable objects remains a challenge within robotics due to the difficulties of
state estimation, long-horizon planning, and predicting how the object will deform given an …

Pneumatic soft robots present many advantages in manipulation tasks. Notably, their
inherent compliance makes them safe and reliable in unstructured and fragile environments …

Deformable objects manipulation can benefit from representations that seamlessly integrate
vision and touch while handling occlusions. In this work, we present a novel approach for …

Multi-task learning of deformable object manipulation is a challenging problem in robot
manipulation. Most previous works address this problem in a goal-conditioned way and …

Autonomous fabric manipulation is a challenging task due to complex dynamics and
potential self-occlusion during fabric handling. An intuitive method of fabric-folding …

In this letter, we present a visual control framework for accurately positioning feature points
belonging to the surface of a 3D deformable object to desired 3D positions, by acting on a …

Goal-conditioned rearrangement of deformable objects (eg straightening a rope and folding
a cloth) is one of the most common deformable manipulation tasks, where the robot needs to …