Fast Contact

Fast contact in robotics focuses on understanding and controlling interactions between robots and their environments, aiming to improve manipulation, locomotion, and human-robot interaction. Current research emphasizes developing robust models for contact dynamics, often employing techniques like physics-encoded graph neural networks, transformer-based decoders, and optimal control formulations, alongside deep learning methods for sensorless contact estimation. This work is crucial for advancing robotic capabilities in diverse applications, from surgical procedures and assembly tasks to safe human-robot collaboration and improved locomotion strategies for legged robots.