Shared Control

Shared control systems aim to seamlessly integrate human input with autonomous robot control, enhancing performance and safety in various applications. Current research focuses on developing adaptive algorithms, such as those based on dynamical systems, reinforcement learning (e.g., TD3), and game-theoretic approaches (e.g., Stackelberg games), to better model human behavior and dynamically adjust the level of autonomy. This field is significant for improving assistive technologies (e.g., robotic arms, wheelchairs), human-robot collaboration in complex tasks (e.g., teleoperation, automated driving), and brain-computer interfaces, ultimately leading to more intuitive and effective human-robot interaction.