Variable Stiffness

Variable stiffness research focuses on developing systems and materials that can dynamically adjust their rigidity, mimicking the adaptability of biological systems. Current efforts concentrate on improving control algorithms, often employing dynamical systems models and reinforcement learning, to achieve precise stiffness modulation in diverse applications like robotics and soft grippers. This work is significant for advancing robotics capabilities, particularly in areas requiring safe and adaptable interaction with unstructured environments, and for creating more biomimetic and efficient designs. The development of accurate models for predicting and controlling variable stiffness is a key challenge driving ongoing research.