Course Outline
Special Topics in Mobile Robots and Self-Driving Cars
This course introduces students to localization, mapping, planning and control of mobile robots and self-driving cars from the probabilistic perspective. Topics include recursive state estimation, Gaussian filters, non-parametric filters, robot motion and perception, localization, mapping, SLAM (simultaneous localization and mapping), obstacle avoidance, navigation, and so on. Laboratory assignments provide hands-on experience with servo drives, sensors, interface circuitry, and microprocessor-based real-time control, Robot Operating System (ROS) programming. Students will fabricate working robotic systems in a group-based term project.
Control Systems II
This course is a continuation of control systems (I). It particularly provides the students with basic knowledge in state-space design, digital control and nonlinear systems. As for the state-space design, it begins with reviewing linear-algebra fundamentals and introducing state-space description of linear systems. Students will then learn how to design full-state feedback and estimator of the control system. In digital control, z-transform will be introduced first and controller design using digital equivalents will then be covered. Finally, we will introduce some basic analysis and design tools for nonlinear control systems.
Digital Control System
This course provides the students with basic knowledge in discrete-time control systems. It covers the introduction of discrete-time systems, z-transform, sampling and reconstruction, open-loop/closed-loop discrete-time systems, time-response characteristics, stability analysis techniques, and digital controller design in both classic control and modern control settings. Students will also learn how to apply control theory to engineering problems via Matlab simulations and Lab assignments.
Robotics
This course provides an overview of robot mechanisms, dynamics, and intelligent controls. Topics include actuators, and sensors, planar and spatial kinematics, multi-rigid-body dynamics, motion planning, control design, and so on. Laboratory assignments provide experience with servo drives, sensors, interface circuitry, construction of a robot arm, microprocessor-based real-time control, and robot operating system (ROS). At the end of the course, students will be competing in groups to complete a robotics challenge.