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 READING OUT DUE 1 08-29 Introduction (.pdf)LAB - Teleoperation GIR 1.1About ROSPRR CH. 1 (S) PA0 08-31 ROS Command Line (.pdf)ROS Cheat Sheet (.pdf)LAB - ROS Command Line SyllabusVideoGIR 2.3-2.7ROS Core ComponentsPRR CH. 2 (S)GIR 2.1-2.2 (S) 2 09-05 rocket_bot.pythruster_w_globals.pythruster_oo.pythruster_oo_responder.pyLAB - Python Publishers and Subscribers VideoROS Tutorial 12PRR CH. 3 (S) 09-07 LAB - ROS Packages ROS Tutorials 3 & 4git tutorialgithub tutorial 3 09-12 LAB - PID Control PID Tutorial (pdf)VideoPID Wikipedia (S)ROS Tutorials 7 & 8rospy parameter tutorial PA1 PA0 (9/11 5:00PM) 09-14 LAB - Numpy Sentry Linear Algebra VideoLinear Algebra Review and Reference (.pdf)sections 1-3.7, (skip 3.6)Numpy tutorial (only the numpy section)Fast Numpy VideoIntro to Numpy and Scipy (S) (.pdf) 4 09-19 Coordinate Systems Coordinate Frame Tutorial (.pdf)Jennifer Kay Kinematics Tutorial (.pdf)(Just sections 6-7) hw1.pdftransforms.pykinematics_hw.py 09-21 The tf Systemtf_demo.pytf2_demo.py Video about tftf Overview 5 09-26 Probability (.pdf) Bayesian Brain, Doya et.al (.pdf)CH 1.1-1.2, 1.4-1.4.3VideoSet Theory Video (S)Bayesâ€™ Rule Video (S) Hw1 (9/26 5:00PM) 09-28 Start LocalizationLocalization (.pdf)Covariance Matrices +Multivariate Gaussian Distribution (.pdf) Bayesian Filtering for Location Estimation, Fox et.al. (.pdf)p. 10-13Mutltivariate Statistics Tutorial6.5.1, 6.5.4-6.5.4.2 HW2 (.pdf) 6 10-03 Kalman Filter (.pdf)kalman.pyplot_gaussians.pykalman_demo.py Kalman Filter TutorialAn Introduction to the Kalman Filter (S) Bibliography PA1 (10/2 5:00PM) 10-05 Localization - Particle Filter (.pdf)particle_demo.pyROS Navigation Lab Particle Filter Explained without EquationsBayesian Filtering for Location Estimation, Fox et.al. (.pdf)p. 13-15 7 10-10 Midterm Review HW2 (10/9 5:00PM) 10-12 MIDTERM 8 10-17 Mapping and SLAMMapping and SLAM (.pdf) Computational Principles of Mobile Robotics9.2.2-9.2.3 PA2 10-19 ROS Navigation (.pdf)ROS Navigation Lab actionlib documentation 1-5, 6.2 9 10-24 Configuration Spaces (.pdf) Computational Principles of Mobile RoboticsCH 6-6.3.2Configuration Space VisualizationConfiguration Space Videos (s) Final Project PA2A (10/23) 10-26 Discrete Path Planning Computational Principles of Mobile Robotics 6.3.3 10 10-31 Randomly Exploring Random Trees (.pdf) Rapidly-exploring random trees: A new tool for path planning S. M. LaValle, 1998 PA2B(10/30)Bibliography (11/5) 11-02 Computer Vision (.pdf)convolutions.pyOpenCV Lab ConvolutionsPython OpenCV IntroOpenCV Basic OperationsOpenCV imagesOpenCV VideoOpenCV Drawing (s)Computer Vision: Algorithms and ApplicationsCH 1 (s) 11 11-07 Object Recognition (.pdf)histogram.pysift_demo.py Computer Vision: Algorithms and Applications CH 4-4.1.3 HW3 (.pdf) Checkpoint 1 (11/7) 11-09 ROS Vision Lab Deep Learning (Accessible from JMU network) 12 11-14 Finish VisionPaper Presentations Checkpoint 2 (11/17 5:00PM) 11-16 Paper PresentationsControl Architectures 13 11-21 THANKSGIVING 11-23 THANKSGIVING 14 11-28 Paper Presentations and Final Project Work 11-30 Paper Presentations and Final Project Work 15 12-05 Paper Presentations and Final Project Work Checkpoint 3 (12/04) 12-07 Exam 12-12 Final Project Presentations 10:30-12:30