Autonomous Mobile Manipulation
( Robotics )

Syllabus & Homework

Syllabus.docx
Homework_1.docx

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 20: State Estimation: SLAM Graph Optimization

Lecture 21: SLAM Smoothing, Fixed-Lag, Keyframe-based