Soft Robot

Soft robotics focuses on creating robots from flexible materials, enabling safer and more adaptable interaction with unstructured environments. Current research emphasizes developing accurate models for control, often employing neural networks (like recurrent neural networks and Echo State Networks), physical reservoir computing, and data-driven methods such as Lagrangian Operator Inference and Proper Orthogonal Decomposition for model reduction. This field is significant due to its potential applications in diverse areas like minimally invasive surgery, search and rescue, and underwater exploration, driving advancements in both robotics and materials science.