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Intelligent robotics labs


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 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 plagiarism will be mercilessly punished ;-).

We strongly urge each student to read 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).


č.t. date E/O outline additional material readings
25.02.2016 1. E Intro, ML estimate HW1, ML_u_v.mat https://en.wikipedia.org/wiki/Overdetermined_system
03.03.2016 2. O 2D localisation reconstruction and SLAM by Least Squares HW2,K.mat, blkdiag2.m řešení přeurčených soustav lineárních rovnic
10.03.2016 3. E Camera and its calibration Homogeneous Least Squares U.mat, X.mat, kinect_k.mat rgbd.mat HW3 plot_pointcloud.m camera model
17.03.2016 4. O 2D localisation by Non-linear Least Squares D.mat HW4.pdf Bonus.pdf lsq-nlsq.pdf
24.03.2016 5. E Classification and ROC curve. HW5: Draw ROC. data.mat bayes.pdf
31.03.2016 6. O Planning optimal area coverage HW6 A.mat E.mat cvxbook
07.04.2016 7. E Reinforcement learning HW7, lab codes Just the basics 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
courses/a3m33iro/labs_en.txt · Last modified: 2016/04/14 09:16 by zimmerk