Syllabus

Autonomous Robotic Systems / Syllabus

 

Date Content Readings Slides Background
Information
Output
07/02 Course Introduction; Model-based & Model-free approaches; Swarm robotics; Introduction to ROS CH1_Bekey
Chapter 1 of the textbook (Thrun et al.)
ROS_paper
Introduction to ROS Installation Instructions
ROS_Tutorials
Programming Robots with ROS
Companion code of the “Programming Robots with ROS” book
Learning ROS for Robotics
Programming
Assignment #1: Swarm robotics
Due: 13/02 at 23:59
14/02 Genetic Algorithms; Central Pattern Generators; Particle Swarm Optimization vs GA Assignment #2: Genetic Algorithms
Due: 06/03 at 23:59
21/02 GA + Learning; Optimizing Body and Mind
07/03 Bayes Filter; Kalman Filter; Localization bayes-location-ubicomp-03
fox2003bayesian
fox98active
Chapter 2 of the textbook (Thrun et al.)
kalman_intro
maybeck_ch1
Chapter 3 of the textbook (except 3.4 and 3.5)
Lecture2part1
lecture2part2
Kalman original paper (1960)
Notes on Univariate Gaussian Distributions and One-Dimensional Kalman Filters
Assignment #3: Bayes Filter
Due: 20/03 at 23:59
14/03 Motion & Sensor Models; Particle Filter Chapters 5 and 6 of the textbook; particle-chapter
particletutorial2
Chapter 4 of the textbook, starting from 4.3
Chapter 8 of the textbook, 8.3.1 and 8.3.2
lecture1okt122
Lecture2part1
lecture2part2
21/03 SLAM Chapter 10 of the textbook lecture_slam
SLAM
Assignment #4: Particle Filter
Due: 27/03 at 23:59
28/03 Exam Preparation