Interaction Control

Interaction control research focuses on enabling robots, AI agents, and other systems to interact effectively and safely with their environments and users, achieving desired outcomes through precise manipulation and responsive adaptation. Current efforts concentrate on developing robust control algorithms, including those based on Gaussian processes, reinforcement learning, and differential games, to manage complex interactions and handle multiple control inputs, often within model-based frameworks. These advancements are crucial for improving human-robot collaboration, enabling more sophisticated autonomous systems, and creating intuitive interfaces for interacting with complex software and hardware.