3 accepted papers
Deformable Linear Objects (DLOs), such as cables and ropes, pose significant challenges for robotic manipulation due to their high-dimensional state space, nonlinear deformation dynamics, and strong sensitivity to external forces. Cable routing tasks, in particular, are further complicated by geomet…
Graph neural networks (GNNs) have been demonstrated to be powerful tools for analyzing structural graph data. However, most existing methods usually rely on fixed adjacency structures for information propagation, lacking strong adaptability to the latent semantic relationships that exist but are not…
Learning robust and generalizable manipulation skills from few demonstrations remains a key challenge in robotics, with broad applications in industrial automation and service robotics. Although recent imitation learning methods have achieved impressive results, they often require a large amount of