Elastomer Deformation

Elastomer deformation research focuses on accurately modeling and simulating the behavior of soft materials under stress, primarily to improve robotic manipulation and tactile sensing. Current efforts concentrate on developing efficient and versatile simulation methods, employing techniques like mesh-free approaches, implicit neural networks, and the Material Point Method (MPM), often coupled with machine learning for improved accuracy and speed. These advancements are crucial for enhancing the realism and reliability of robotic systems, particularly in applications like surgery and manufacturing quality control, where precise interaction with deformable objects is essential.