This lecture introduces fundamental concepts and methodologies for human assistive robotics, focusing on robot systems designed to augment, rehabilitate, or assist human motion. Human assistive robots must interact seamlessly with human biomechanics, requiring an understanding of human motion mechanisms, biomechanical modeling, and bio-signal processing. To address these challenges, this course first explores human motion mechanisms, including muscle, tendon, and joint dynamics, as well as human motion control theory. Next, it covers the mechanical design of assistive robots, considering the mechanism of human. The integration of bio-signals, such as EMG and EEG, into robotic control is also introduced, along with analytical methods for motion analysis. Finally, this course delves into control strategies for assistive robots, including state estimation, motion trajectory generation, force-based control methods, and human-in-the-loop optimization. Through theoretical foundations and practical demonstrations, this course provides students with a comprehensive understanding of designing and controlling human assistive robotic systems.

This lecture introduces general concepts for control of a class of linear systems. The “linear” system does not only mean an ideal system described by equations of motions, but also includes an actual mechanical system, the dominant dynamic behavior of which can be assumed to be linear. In order to deal with linear systems, this lecture first introduces linear system theory for understanding and modeling of linear systems. Linear control theory including state space descriptions, controllability/observability, transfer functions, time-domain analysis and stability are then introduced. The real-world systems, however, always show uncertainties in the dynamic characteristics, and thus this lecture also introduces robust control theory, such as small gain theorem and H-infinity optimal control, for dealing with systems with uncertain dynamics. In this course, various numerical and mathematical methods will be introduced to design control algorithms.

This course is a comprehensive introduction to control system synthesis in which the digital computer plays a major role. The course covers elements of real-time computer architecture; input-output interfaces and data converters; analysis and synthesis of sampled-data control systems using classical and modern (state-space) methods; analysis of trade-offs in control algorithms for computation speed and quantization effects. In addition to the fundamental theory in digital system control, this course introduces advanced control techniques such as discrete-time linear quadratic control, adaptive control, parameter adaptation, repetitive control, learning control, and so on. Homework includes computer simulations where students can experience practical digital servo interfacing and implementation problems with timing, noise, and other practical issues.

Although the beauty of control theories attracts many engineers, the inherent limitations of control theories are unavoidable in practice. Most of the control theories assume that a plant is given and seek a solution to obtain the desired performance by suggesting an appropriate control algorithm. RSC Lab’s research issues are all based on a fundamental question that the application of control theories should start from the beginning of mechanical design. Namely, the mechanical system should be designed considering the controllability and observability of the plant, such that the system has the minimal limitations in the controller design. Also, the controller design process should suggest both control parameters and mechanical design parameters for obtaining the most effective and energy-efficient control performance. Therefore, students of RSC Lab learn both the mechanical design and control theories in an integrated way. This education philosophy may be different from typical educations in the field of Mechatronics or Robotics in a viewpoint that it deals with the interdisciplinary cross-application of the mechanical design and control theories.