Readings followed by (S) are supplemental. You should read them, but you won't be tested on that material.
| WEEK |
DATE |
TOPIC |
READING |
OUT |
DUE |
| 1 |
01-13 |
Introduction (.pdf) / Syllabus
LAB 1 - Gazebo |
About ROS
ROS Concepts (s) |
HW1 |
|
|
01-15 |
LAB 2 - Wander |
Syllabus
GIR 2.1-2.2 (s)
GIR 2.3-2.7
ROS Tutorial 12 |
|
| 2 |
01-20 |
LAB 3 - Python Publishers and Subscribers |
ROS Tutorial 12 (Review) |
|
HW #1 (1/23 5:00PM) |
|
01-22 |
LAB 4 - Creating ROS Packages |
ROS Tutorials 3 & 4
Mercurial Tutorial 1
Mercurial Tutorial 2 |
PA1 |
| 3 |
01-27 |
PID Controllers (.pdf)
pid.py
pid_demo.py
LAB 5 |
ROS Tutorials 7 & 8
Wikipedia: PID Controllers 1-3 |
|
|
|
01-29 |
Kinematics
transforms.py |
Introduction to Homogeneous Transformations & Robot Kinematics
Linear Algebra Video (s) |
HW2 (.pdf)
kinematics_hw.py |
| 4 |
02-03 |
tf_demo.py
ROS Rotations
ROS Coordinate Frames
LAB 6 - Simple Navigation and tf |
Intro. to Numpy and Scipy (.pdf)
(p 1-11, 16-17)
Video about tf
tf Overview page |
|
PA1 (Monday 2/2, 11:59PM)
HW2 (Friday 2/6, 5:00PM) |
|
02-05 |
Start Probability |
Video
Slides (.pdf)
Learning Occupancy Grid Maps with Forward Sensor Models
(SECTION 2 ONLY) |
HW3 |
| 5 |
02-10 |
ASSESSMENT DAY |
|
|
HW3 (Thursday, 11:00AM) |
|
02-12 |
ROS Mapping and Navigation (.pdf)
LAB Turtlebot Mapping |
|
PA2 |
| 6 |
02-17 |
|
Bayesian Filtering for Location Estimation (.pdf)
Fox et. al., 2003. p. 10-13 |
|
|
|
02-19 |
Recursive State Estimation (.pdf)
The Kalman Filter (.pdf)
kalman.py
kalman_demo.py
plot_gaussians.py |
Kalman Filter Tutorial (1-14)
An Introduction to the Kalman Filter (s) |
HW4 (.pdf) |
| 7 |
02-24 |
Continue Kalman Filter |
|
|
PA2 (2/26, 11:59PM) |
|
02-26 |
Particle Filters |
Particle Filter Explained without Equations
Bayesian Filtering for Location Estimation (.pdf)
Fox et. al., 2003. p. 13-15 |
|
| 8 |
03-03 |
Control Architectures |
Gat, Erann. "On three-layer architectures." Artificial intelligence and mobile robots (1998): 195-210.
http://wiki.ros.org/smach |
|
Final Project Proposal (3/3 11:00AM)
HW4 (3/3 11:00AM) |
|
03-05 |
SNOW DAY |
|
|
| 9 |
03-10 |
SPRING BREAK |
|
|
|
|
03-12 |
SPRING BREAK |
|
|
| 10 |
03-17 |
MIDTERM |
|
|
|
|
03-19 |
Computer Vision Intro (.pdf)
plot_pixels.py |
Python OpenCV Intro
OpenCV Basic Operations
OpenCV images
OpenCV Video
OpenCV Drawing (s)
Computer Vision: Algorithms and Applications
CH 1 (s) |
|
| 11 |
03-24 |
Color Histograms
histogram.py
OpenCV Lab |
OpenCV Color Histogram Tutorial
Indexing Via Color Histograms
(Swain and Ballard, 1990) |
|
Checkpoint #1 (3/23, 11:00PM) |
|
03-26 |
Object Detection
ROS Vision Lab |
Computer Vision: Algorithms and Applications
CH 4-4.1.3 |
|
| 12 |
03-31 |
Configuration Spaces (.pdf) |
Computational Principles of Mobile Robotics
CH 6-6.3.2
Configuration Space Visualization
|
Annotated Bibliography |
Checkpoint #2 (4/2 11:00PM) |
|
04-02 |
Discrete Path Planning (.pdf) |
Computational Principles of Mobile Robotics
CH 6.3.3
Thrun A* Videos 12-14, 20, 23 |
|
| 13 |
04-07 |
Rapidly-Exploring Random Trees |
Rapidly-exploring random trees: A new tool for path planning. S. M. LaValle, 1998
RRT Demos and information (s) |
HW5 (.pdf) |
Annotated Bibliography (4/9 11:00PM) |
|
04-09 |
SLAM
|
Computational Principles of Mobile Robotics
9.2.2-9.2.3 |
|
| 14 |
04-14 |
Control Architectures |
Computational Principles of Mobile Robotics
CH 7 - 7.5.0
Gat, Erann. "On three-layer architectures." Artificial intelligence and mobile robots (1998): 195-210. |
|
Checkpoint #3 (4/16 11:00PM) |
|
04-16 |
Paper Presentations and Final Project Work |
|
|
| 15 |
04-21 |
Paper Presentations and Final Project Work |
|
|
HW5 (4/21 11:00AM)
Checkpoint #4 (4/23 11:00PM) |
|
04-23 |
Paper Presentations and Final Project Work |
|
|
| 16 |
04-28 |
Review for Final |
|
|
|
|
04-30 |
Final Project Presentations |
|
|
|
05-05 |
Final 8:00-10:00 |
|
|
|
