CS354 Schedule

Readings followed by (S) are supplemental. You should read them, but you won't be tested on that material.

Readings labeled "GIR" are from A Gentle Introduction to ROS. Jason M. O'Kane. 2014.

Readings labeled "PRR" are from Programming Robots with ROS . Morgan Quigley, Brian Gerkey, William D. Smart. 2015.

WEEK	DATE	TOPIC	READING	OUT	DUE
1	08-30	Introduction (.pdf) LAB - Teleoperation	GIR 1.1 About ROS PRR CH. 1 (S)	PA0
	09-01	ROS Command Line (.pdf) LAB - ROS Command Line	Syllabus GIR 2.3-2.7 ROS Core Components PRR CH. 2 (S) GIR 2.1-2.2 (S)
2	09-06	rocket_bot.py thruster_w_globals.py thruster_oo.py thruster_oo_responder.py LAB - Python Publishers and Subscribers	ROS Tutorial 12 PRR CH. 3 (S)
	09-08	LAB - ROS Packages	ROS Tutorials 3 & 4 git tutorial github tutorial
3	09-13	LAB - PID Control	PID Tutorial (pdf) PID Wikipedia (S) ROS Tutorials 7 & 8 rospy parameter tutorial	PA1	PA0 (9/12 5:00PM)
	09-15	Linear Algebra + Numpy LAB - Numpy Sentry	Numpy tutorial (only the numpy section) Intro to Numpy and Scipy (S) (.pdf) Linear Algebra Video (S)		PA0 (9/12 5:00PM)
4	09-20	Coordinate Systems and Kinematics Coordinate Systems	Coordinate Frame Tutorial (.pdf) Jennifer Kay Kinematics Tutorial (.pdf) (Just sections 6-7)	hw1.pdf transforms.py kinematics_hw.py
	09-22	The tf system	Video about tf tf Overview
5	09-27	Probability (.pdf)	Bayesian Brain, Doya et.al (.pdf) CH 1.1-1.2, 1.4-1.4.3 Set Theory Video (S) Bayes’ Rule Video (S)		Hw1 (9/27 5:00PM)
	09-29	Localization (.pdf) Covariance Matrices +Multivariate Gaussian Distribution (.pdf)	Bayesian Filtering for Location Estimation, Fox et.al. (.pdf) p. 10-13 Mutltivariate Statistics Tutorial 6.5.1, 6.5.4-6.5.4.2	HW2 (.pdf)	Hw1 (9/27 5:00PM)
6	10-04	Kalman Filter (.pdf) kalman.py plot_gaussians.py kalman_demo.py	Kalman Filter Tutorial (1-14) An Introduction to the Kalman Filter (S)		PA1 (10/3 5:00PM) HW2 (10/6 5:00PM)
	10-06	Particle Filter Localization - Particle Filter (.pdf) ROS Navigation Lab	Particle Filter Explained without Equations Bayesian Filtering for Location Estimation, Fox et.al. (.pdf) p. 13-15		PA1 (10/3 5:00PM) HW2 (10/6 5:00PM)
7	10-11	particle_demo.py Midterm Review
	10-13	MIDTERM
8	10-18	Mapping and SLAM (.pdf)	Computational Principles of Mobile Robotics 9.2.2-9.2.3	PA2 Bibliography
	10-20	ROS Navigation Stack ROS Navigation (.pdf) ROS Navigation Lab	actionlib documentation 1-5, 6.2
9	10-25	Configuration Spaces (.pdf)*	Computational Principles of Mobile Robotics CH 6-6.3.2 Configuration Space Visualization		PA2A (10/24)
	10-27	Discrete Path Planning	Computational Principles of Mobile Robotics 6.3.3		PA2A (10/24)
10	11-01	Continue Path Planning			PA2B(10/31)
	11-03	Randomly Exploring Random Trees (.pdf)	Rapidly-exploring random trees: A new tool for path planning S. M. LaValle, 1998	Final Project	PA2B(10/31)
11	11-08	Computer Vision Computer Vision (.pdf) convolutions.py OpenCV Lab	Python OpenCV Intro OpenCV Basic Operations OpenCV images OpenCV Video OpenCV Drawing (s) Computer Vision: Algorithms and ApplicationsCH 1 (s)	HW3 (.pdf)	Bibliography (11/7)
	11-10	ROS Vision Lab			Bibliography (11/7)
12	11-15	Object Recognition (.pdf) histogram.py sift_demo.py	Computer Vision: Algorithms and Applications CH 4-4.1.3 Deep Learning (Accessible from JMU network)		Checkpoint 1 (11/14 5:00PM)
	11-17	Control Architectures			Checkpoint 1 (11/14 5:00PM)
13	11-22	THANKSGIVING
	11-24	THANKSGIVING
14	11-29	Paper Presentations and Final Project Work			Checkpoint 2 (12/01 5:00PM)
	12-01	Paper Presentations and Final Project Work			Checkpoint 2 (12/01 5:00PM)
15	12-06	Paper Presentations and Final Project Work
	12-08	Paper Presentations and Final Project Work
	12-15	Final Exam 10:30-12:30