Foundations of interaction control for contact robots:
Energy-based methods and interactive learning

In recent decades, the proliferation of contact robots—designed to physically interact with humans—has revolutionized applications ranging from personalized assistance to physical training and rehabilitation. These robots, which engage in complex tasks such as facilitating teamwork or providing resistance in task-oriented movements, require control mechanisms that ensure safe, intuitive, and efficient interactions with both their human users and the environment. Designing such optimal interactions necessitates an understanding of human sensorimotor behavior and the use of advanced control strategies. This tutorial on "Foundations of interaction control for contact robots" will thus include the following key topics:

• Nonlinear stochastic optimal control for modeling of human motor behaviors, considering the inherent variability and noisy sensory signals.

• Haptic communication strategies based on observations of human cooperative tasks, emphasizing prediction and adaptation to enhance performance and learning. 

• The application of passivity theory to manage energy exchanges in physically interactive systems.

• Differential game theory for crafting cooperative strategies among participants with distinct roles.

This body of work, to which we have significantly contributed, forms a comprehensive framework for understanding and modeling sensorimotor interactions between humans, designing intuitive and optimal human-robot interaction strategies, and coordinating multiple robots. Participants will gain insights into these techniques and learn how to apply and expand upon them in various robotics and human-centric applications.