Karel Zimmermann is the second lecturer of ARO and head of the labs. | |
Tomas Petricek is the ICP SLAM lab tutor. | |
Vojtech Salansky is the Deep learning lab tutor. | |
Radoslav Škoviera is the exploration and path planning tutor. | |
Ondřej Holešovský is the waypoint navigation tutor. |
Labs takes place in E-128 every Tuesday and Thursday. Labs consist of 7 regular labs intended for practical exercises, 5 lessons intended for semestral work consultations, last two labs are intended for semestral work demonstrations. Participation in the regular labs and in one of the demonstration lab is mandatory. The content of regular labs is the implementation of a solution to a defined problem such as localization, planning or object detection (see the program for details). Solution to the problem has to be demonstrated to the lab tutor not later than 7 days after the labs at which it was assigned. If a correct solution of the problem is demonstrated before homework deadline, the solution is rewarded by 3 points, There will be 6 such homeworks, therefore you can obtain 18 points from regular labs in total. The code containing your solution of the homework should be uploaded via the upload system. If no homework is assigned, the 3 points are provided for participation.
We want students to work individually, therefore any kind of plagiarism in codes, homeworks or reports will be mercilessly punished . We strongly urge each student to read what is/isnot plagiarism - we believe that many students 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:
č.t. | date | tutor | labs plan | links |
---|---|---|---|---|
1 | 19.2./21.2. 2019 | Rado | Intro to Python | slides |
2 | 26.2./28.2. 2019 | Rado | Intro to ROS | slides homework HW_bagfile |
3 | 5.3./7.3. 2019 | Tomas | ICP SLAM | tf_slides.pdf, icp_slam_slides.pdf icp_slam.pdf (homework instructions), icp_slam.zip (source codes) |
4 | 12.3./14.3. 2019 | Rado | Planning and exploration | slides homework template source files |
5 | 19.3./21.3. 2019 | Ondra | Waypoint navigation + TurtleBot intro + semestral work assignment | robot_coordination_v3.tar.gz |
6 | 26.3./27.3. 2019 | Vojta | Deep Learning I (PyTorch) | slides scripts pretrained_weights training_dataset validation_dataset |
7 | 2.4./4.4. 2019 | Vojta | Deep Learning II (Object detection) | ws package how to use rosbag |
8 | 9.4./11.4. 2019 | Ondra | Semestral work | |
9 | 16.4./18.4. 2019 | Tomas | Semestral work | |
10 | 23.4./25.4. 2019 | Vojta | Semestral work | |
11 | 30.4./2.5 2019 | Vojta | Semestral work | |
12 | 7.5./9.5. 2019 | Ondra | Semestral work | |
13 | 14.5./16.5. 2019 | Karel+Rado+Ondra | First demonstration of semestral works | |
14 | 21.5./23.5. 2019 | Karel+Vojta | Second demonstration of semestral works + credit |