Fast Robots @ Cornell, Spring 2023

Lecture slides

Lecture slides will be uploaded on this page. Recorded lectures are available via Canvas.

• Lecture 1 - Intro
• Lecture 2 - Transformation Matrices
• Lecture 3 - Sensors I
• Lecture 4 - Sensors II / IMU, code ‘
• Lecture 5 - EMI and Wiring, worksheet
• Lecture 6 - Batteries and Actuators
• Lecture 7 - PID control ‘’
• Lecture 8 - PID control, continued, worksheet
• Lecture 9 - Linear systems, recap
• Lecture 10 - Controllability
• Lecture 11 - Controllability/LQR
• Lecture 12 - Probability and Bayes Theorem
• Lecture 13 - Observability and Kalman Filters
• Lecture 14 - Local Planning and Map Representations
• Lecture 15 - Maps, Graph construction and Graph search
• Lecture 16 - Markov and Bayes Filter I
• Lecture 17 - Motion models
• Lecture 18 - Sensor models
• Lecture 19 - Bayes Filter II
• Lecture 20 - Simulator
• Lecture 21 - Particle Filters and intro to SLAM
• Lecture 22 - Ethics I
• Lectures 23 - Ethics II

’ This code was uploaded at a random point during an interactive lecture, feel free to check it out, but use with caution!

’’ Note: since this lecture was covered by Jonathan, these slides are from last year.