Object Deformation

Object deformation research focuses on accurately modeling and predicting how objects change shape under external forces, a crucial challenge for robotics, computer graphics, and material science. Current efforts concentrate on developing robust and generalizable models, employing techniques like implicit neural representations, graph neural networks, and Gaussian splatting to capture complex deformations from various data sources (e.g., visual and tactile feedback). These advancements are improving robotic manipulation of deformable objects, enabling more realistic simulations, and facilitating accurate deformation classification in diverse applications such as structural health monitoring.