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Autonomous Robotics Labs

Semestral work localization error

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Lecturers

http://cmp.felk.cvut.cz/~zimmerk Karel Zimmermann is the second lecturer of ARO and head of the labs.
http://cmp.felk.cvut.cz/~petrito1 Tomas Petricek is the ICP SLAM lab tutor.
http://cmp.felk.cvut.cz/~salanvoj/ Vojtech Salansky is the Deep learning lab tutor.
http://people.ciirc.cvut.cz/skovirad/ Radoslav Škoviera is the exploration and path planning tutor.
http://people.ciirc.cvut.cz/holesond/ Ondřej Holešovský is the waypoint navigation tutor.

Outline

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:

  • Uploading own solution of the semestral report (reports) before the beginning of the labs in the thirteenth week.
  • Demonstration of own solution of the semestral work in the fourteenth week.
  • Showing own solution of all homework before the beginning of the labs in the thirteenth week.
  • Obtaining at least 20 points (out of 40 possible).

Program

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
courses/aro/tutorials/start.txt · Last modified: 2019/06/03 13:07 by zimmerk