In this course, a broad and practical overview for robotics is given in a multi-disciplinary perspective. Key principles such as coordinate transformation, navigation, control, motion planning, and decision making are taught. Recent advances in drons, self-driving cars, and AI for robotics are also introduced.
This course is an introduction to continuous-time and discrete-time signals and systems. The course covers Fourier series, Fourier transform, Laplace transform, and z-transform. Various types of systems with emphasis on linear time invariant system is studied.
This course will cover general methods for analysis and design of the dynamic system. The main contents include modeling in the frequency and time domain, time response, reduction of multiple subsystems, stability, steady-state error, root locus technique, frequency response technique, and design via frequency response and state-space.