Variable Impedance Control

Variable impedance control (VIC) allows robots to dynamically adjust their stiffness and damping during interaction with the environment, enabling safer and more adaptable manipulation. Current research focuses on learning-based approaches, often employing neural networks and model predictive control (MPC) to optimize impedance parameters for various tasks, including human-robot collaboration and contact-rich manipulation. These advancements are driven by the need for robots to safely and effectively interact with unpredictable environments and humans, with applications ranging from industrial automation to assistive robotics and medical procedures. The integration of passivity-based control strategies ensures safe energy exchange during interaction, enhancing robustness and reliability.