Syllabus & Homework
Lecture Slides
Lecture 1 : Introduction
Lecture 2: Coordinate Systems
Lecture 3: Rigid Body Motion
Lecture 4: Wrenches and Actuation
Lecture 5: Rigid Body Kinematics and Dynamics
Lecture 6: Wheeled Robot Kinematics
Lecture 7: Guidance: Open-Loop, Feedback-driven
Lecture 8: L1 Guidance, Pure Pursuit, Stanley Controller
Lecture 9: Control Fundamentals
Lecture 10: Control: LTI Systems
Lecture 11: Control: Model Predictive Control
Lecture 12: Manipulation: Forward Kinematics, Manipulability
Lecture 13: Manipulation: Inverse Kinematics, Trajectory Generation
Lecture 14: Planning Fundamentals
Lecture 15: Planning: Graph-based, Dijkstra, A*
Lecture16: Planning: Sampling-based, PRM, sPRM, PRM*, RRT
Lecture17: Planning: Sampling-based, RRT*
Lecture 18: Sensors
Lecture 19: State Estimation: Bayesian Estimation - Kalman Filter
Lecture 20: State Estimation: SLAM Extended Kalman Filter
Lecture 21: SLAM Unscented Kalman Filter, Particle Filter
Lecture 22: State Estimation: SLAM Graph Optimization
Lecture 23: SLAM Smoothing, Fixed-Lag, Keyframe-based