====== Intelligent robotics labs ====== * [[https://cw.felk.cvut.cz/ulohy/ | Upload system ]] * [[http://www.fel.cvut.cz/cz/education/rozvrhy-ng.B152/public/cz/predmety/12/81/p12816004.html|Schedule]] * Lab teachers: * [[http://cmp.felk.cvut.cz/~zimmerk/|Karel Zimmermann]] (Head of labs) * [[http://cmp.felk.cvut.cz/~peckama2/|Martin Pecka ]], * [[https://sites.google.com/site/kubelvla/|Vladimír Kubelka ]], * [[http://cmp.felk.cvut.cz/~wagnelib/Libor Wágner]], ===== Outline ===== Labs consists of 8 regular labs intended for practical exercises, 5 voluntary lessons intended for semestral work consultations and the final lesson. Participation in the regular and the final lab is mandatory. There will be 7 homeworks assigned during regular labs, which are due to in 7 days. If correct solution of the homework is demonstrated in the following lab, the homework is rewarded by 3 points, i.e. you can obtain 21 points from homeworks in total. Homeworks are not uploaded, it is enough to show the solution in the beginning of the next labs. Semestral work assignment is in the eight week, the solution have to be [[https://cw.felk.cvut.cz/upload/| uploaded]] before beginning of the labs in the thirteen week. You can obtain up to 19 points for the solution. Each student is obliged to upload own code and a short report consisting of the answers to a few questions. Semestral work is solved individually and any kind of [[https://cw.felk.cvut.cz/wiki/help/common/plagiarism_cheating|plagiarism]] will be mercilessly punished ;-). We strongly urge each student to read [[https://cw.felk.cvut.cz/wiki/help/common/plagiarism_cheating| what is/isnot a plagiarism]] - we believe that many student will be surprised. In any case, it is not permitted to use the work of your colleagues or predecessors. Each student is responsible for ensuring that his work does not get into the hands of other colleagues. In the case of multiple submission of the same work, all involved students will be penalized, including those who gave the work available to others. Credit conditions: * Uploading **own** solution of the semestral work before the beginning of the labs in the thirteenth week. * Showing **own** solution of all homeworks before the beginning of the labs in the thirteenth week. * Obtaining at least 20 points (out of 40 possible). ===== Program ===== ^ č.t. ^ date ^ E/O ^ outline ^ additional material ^ readings ^ | 25.02.2016 | 1. | E | Intro, ML estimate | {{:courses:a3m33iro:ml_model_rychlosti.pdf|HW1}}, {{:courses:a3m33iro:ml_u_v.mat|ML_u_v.mat}} | [[https://en.wikipedia.org/wiki/Overdetermined_system | https://en.wikipedia.org/wiki/Overdetermined_system ]] | | 03.03.2016 | 2. | O | 2D localisation reconstruction and SLAM by Least Squares | {{:courses:a3m33iro:2d_slam.pdf|HW2}},{{:courses:a3m33iro:k.mat|K.mat}}, {{:courses:a3m33iro:blkdiag2.m|blkdiag2.m}} | {{:courses:a3m33iro:overdetermined_homogenous_linear_equations.pdf|řešení přeurčených soustav lineárních rovnic}} | | 10.03.2016 | 3. | E | Camera and its calibration Homogeneous Least Squares | {{:courses:a3m33iro:u.mat| U.mat}}, {{:courses:a3m33iro:x.mat| X.mat}}, {{:courses:a3m33iro:kinect_k.mat|}} {{:courses:a3m33iro:rgbd.mat|}} {{:courses:a3m33iro:3d_coloring.pdf|HW3}} {{:courses:a3m33iro:plot_pointcloud.m | plot_pointcloud.m}} | [[http://www.maths.lth.se/matematiklth/personal/calle/datorseende13/notes/forelas1.pdf | camera model]] | | 17.03.2016 | 4. | O | 2D localisation by Non-linear Least Squares | {{:courses:a3m33iro:nlsq_d.mat|D.mat}} {{:courses:a3m33iro:nlsq_2d_lokalizace.pdf|HW4.pdf}} {{:courses:a3m33iro:nlsq_2d_slam.pdf|Bonus.pdf}}| {{:courses:a3m33iro:lsq-nlsq.pdf|}} | | 24.03.2016 | 5. | E | Classification and ROC curve. | HW5: Draw ROC. {{:courses:a3m33iro:data.mat| data.mat}} | {{:courses:a3m33iro:bayes.pdf|bayes.pdf}} | | 31.03.2016 | 6. | O | Planning optimal area coverage | {{:courses:a3m33iro:shortest_path_with_full_coverage.pdf|HW6}} {{:courses:a3m33iro:a_coverage.mat|A.mat}} {{:courses:a3m33iro:E_coverage.mat|E.mat}} | [[http://stanford.edu/~boyd/cvxbook | cvxbook]] | | 07.04.2016 | 7. | E | Reinforcement learning | {{:courses:a3m33iro:hw_rl.pdf|HW7}}, {{:courses:a3m33iro:07_reinf_student.zip|lab codes}} | Just the basics {{:courses:a3m33iro:aima-rl.pdf|}} | | 14.04.2016 | 8. | O | semestral work assignment | | | | 21.04.2016 | 9. | E | //konzultace// | | | | 28.04.2016 | 10. | O | //konzultace// | | | | 05.05.2016 | 11. | E | //konzultace// | | | | 12.05.2016 | 12. | O | //konzultace// | | | | 19.05.2016 | 13. | E | //konzultace// | | | | 26.05.2016 | 14. | O | winner presentation | | |