The study of human-machine interaction as a unique control system has been one of the first research interests in engineering, with nearly a century having passed since the first works in the field. At the same time, it is a crucial aspect of the most recent technological developments in applications of fields such as collaborative robotics and artificial intelligence.
The cross-domain nature characterizing this field of study can cause difficulties in finding a guiding line that links motor control theory, modeling approaches of physiological control systems, and identifying human-machine general control models. In this book, the author aims to find such a guiding line by exploring the existing scientific efforts in these fascinating technological scenarios and proposing a novel approach that could enhance human-robot collaboration and interaction. The book is an academic reference and a practical guide for researchers and students in robotics, control systems, and artificial intelligence. The goal is to offer a combination of foundational theory, methodological innovation, and real-world applications to provide the reader with the insights necessary to implement and put into practice state-of-the-art methodologies in robotic control systems.
Contents:
- Preface
- Introduction
- Linear Models
- Precision Model for Human Reactive Delay Identification in Robotic Manipulation
- Nonlinear Models
- Human Motion Prediction
- NARMAX Model for Human Force Estimation
- Frequency Domain Analysis and Human Reactive Delay Estimation
- Peak-to-Peak Dynamics
- Conclusion
- Appendix
- Bibliography
Readership: For its contents and lexical aspects, the book is mostly suitable to advanced academic environments, where it may interest researchers, teachers, and graduate student that are interested in control and modeling techniques in automation-related fields.