As robots and other intelligent agents move from simple environments and problems to more
complex, unstructured settings, manually programming their behavior has become …

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 …

Manipulating deformable objects is a challenging task for robots. The major difficulty lies in
how to track these objects accurately, robustly, and efficiently, considering they have infinite …

To enhance the robotic manipulation of deformable objects, a robust state estimator is
proposed to track the object configuration in real time. A Gaussian mixture model (GMM) is …

Learning from demonstration by means of non-rigid point cloud registration is an effective
tool for learning to manipulate a wide range of deformable objects. However, most methods …

To perform robot manipulation tasks, a low-dimensional state of the environment typically
needs to be estimated. However, designing a state estimator can sometimes be difficult …

Recent works of non-rigid registration have shown promising applications on tasks of
deformable manipulation. Those approaches use thin plate spline-robust point matching …

We present a new fully-automatic non-rigid 3D shape registration (morphing) framework
comprising (1) a new 3D landmarking and pose normalisation method;(2) an adaptive …

We propose a shape template morphing approach suitable for any class of shapes that
exhibits approximate reflective symmetry over some plane. The human face and full head …

We present a fully-automatic image processing pipeline to build a set of 2D morphable
models of three craniofacial profiles from orthogonal viewpoints, side view, front view and …