The long-promised presence of robots in everyday life cannot be fulfilled by motion alone. Daily life is shaped by physical interaction: from the exchange of forces that supports walking to the contacts through which we act upon and change the world around us.
Robots can be carefully designed and modeled; the world around them cannot. The diversity of objects, contacts, and task conditions calls for interaction paradigms that remain effective without complete environmental models.
This book approaches diverse interaction scenarios by considering force and motion together, rather than treating either one as secondary. Their relation defines the behavior of interaction, while their product exposes the underlying exchange of power and energy. This perspective leads to a passivity-based framework in which robot physical interaction can be modeled, stabilized, and controlled through modular building blocks.
The resulting framework is physics-grounded yet intuitive, offering an interpretable layer on which modern data-driven methods can build. In this way, classical control concepts and emerging learning-based approaches need not be seen as competing alternatives, but as complementary tools for developing reliable robot interaction.
This book presents a unified passivity-based framework for robot physical interaction, addressing the simultaneous control of force and motion, reactive policy design for human-robot scenarios, and energy-based modeling and monitoring. Rather than offering task-specific solutions, it develops a modular architecture grounded in physical principles, enabling robust and generalizable interaction control across diverse real-world settings.
Applications range from industrial manipulation and multi-manual object handling to ergonomic haptic guidance and support-adaptive robot-aided rehabilitation. The latter has been translated into a CE-certified system used in clinical settings worldwide and recognized with the 2021 euRobotics Technology Transfer Award.
The book is intended for researchers and graduate students in robotics, control theory, and human-robot interaction. It provides both rigorous theoretical foundations and practical examples, while offering an interpretable basis for future integration with data-driven and learning-based methods.
Erfan Shahriari
Passivity Tactile Manipulation Unified Force–Impedance Control Port-Hamiltonian Virtual Energy Tanks Phase-Based Planning Human-Robot Interaction Rehabilitation Robotics Manipulability Energy-Aware Control