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 |
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| 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 |
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| 21/03 | SLAM | Chapter 10 of the textbook | lecture_slam SLAM |
Assignment #4: Particle Filter Due: 27/03 at 23:59 |
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| 28/03 | Exam Preparation |