Introduction to Robotics

This graduate course treats a robot as a rigid-body system you can model, command, and close a sensing loop around, working from kinematic chains and dynamics up through trajectory planning and the perception stack that lets mobile platforms localize and avoid obstacles. Expect to spend most of your time deriving D-H parameters, solving inverse kinematics by hand, grinding through Lagrange-Euler and Newton-Euler equations of motion, and producing two mini-projects alongside the midterm and final. It assumes you are comfortable with linear algebra, dynamics, and signals, and serves as the foundation students lean on before moving into control, motion planning, or SLAM-flavored research.