======= Autonomous Robotics Labs ======= ====== Semestral work localization error ====== ^ {{:courses:aro:tutorials:screenshot_2019-05-27_10.14.57.png?400|}}^{{youtube>sLS0B8Sjoxw?medium}} ====== Lecturers ====== |{{:courses:b3b33vir:karel_zimmermann.png?70 |http://cmp.felk.cvut.cz/~zimmerk}} | [[http://cmp.felk.cvut.cz/~zimmerk/|Karel Zimmermann]] is the second lecturer of ARO and head of the labs.| |{{:courses:b3b33vir:tomas_petricek.jpg?70 |http://cmp.felk.cvut.cz/~petrito1}} | [[http://cmp.felk.cvut.cz/~petrito1/|Tomas Petricek]] is the ICP SLAM lab tutor. | |{{:courses:aro:tutorials:vojta_salansky.jpg?70 |http://cmp.felk.cvut.cz/~salanvoj/}} | [[http://cmp.felk.cvut.cz/~salanvoj/|Vojtech Salansky]] is the Deep learning lab tutor. | |{{:courses:aro:tutorials:rado_skoviera.jpg?70 |http://people.ciirc.cvut.cz/skovirad/}} | [[http://people.ciirc.cvut.cz/skovirad/|Radoslav Škoviera]] is the exploration and path planning tutor. | |{{:courses:aro:tutorials:ondrej_holesovsky.png?70 |http://people.ciirc.cvut.cz/holesond/}} | [[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 [[https://cw.felk.cvut.cz/upload/|upload system]]. If no homework is assigned, the 3 points are provided for participation. /*[[https://gitlab.fel.cvut.cz/kubelvla/b3m33aro_semestral|]]* Semestral work assignment is in the eighth week, the solution has to be [[https://cw.felk.cvut.cz/upload/| uploaded]] before the beginning of the labs in the thirteenth week. You can obtain up to 22 points for the solution. Each group of students (maximum size is 3) is obliged to upload own code and a short report describing proposed pipeline. /* consisting of explicit answers to a few questions: Report should consist of answers for the following questions: ”(i) How do you estimate and update the 3D position of the markers? (ii) How do you update the position of the robot in relation to markers? (iii) How do you plan the trajectory for the robot through the course? (iv) How do you execute the planned trajectory? (v) How do you evaluate the progress of proposed solutions?”. The maximum length of the report is three A4 pages containing not more than 2700 characters (i.e. one and a half normalized pages [[https://cs.wikipedia.org/wiki/Normostrana|normostrany]]) and an arbitrary amount of figures (captions are also counted as characters, axis titles are not counted). */ We want students to work individually, therefore any kind of [[https://cw.felk.cvut.cz/wiki/help/common/plagiarism_cheating|plagiarism]] in codes, homeworks or reports will be mercilessly punished ;-). We strongly urge each student to read [[https://cw.felk.cvut.cz/wiki/help/common/plagiarism_cheating| 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). [[courses:aro:tutorials:ros|Guide on how to install ROS on your computer or how to run it on the computers in labs]] [[courses:aro:tutorials:turtlebots|Guide to the TurtleBot robotic lab.]] ===== Program ===== ^ č.t. ^ date ^ tutor ^ labs plan ^ links ^ | 1 | 19.2./21.2. 2019 | Rado | Intro to Python | {{ :courses:aro:tutorials:01_python_ros_intro.pdf | slides}} | | 2 | 26.2./28.2. 2019 | Rado | Intro to ROS | {{ :courses:aro:tutorials:02_ros_intro.pdf | slides}} {{ :courses:aro:tutorials:02_homework.pdf | homework}} {{ :courses:aro:tutorials:2019-02-20-11-00-56.zip | HW_bagfile}} | | 3 | 5.3./7.3. 2019 | Tomas | ICP SLAM | {{ :courses:aro:tutorials:tf_slides.pdf | tf_slides.pdf}}, \\ {{ :courses:aro:tutorials:icp_slam_slides.pdf | icp_slam_slides.pdf}} \\ {{ :courses:aro:tutorials:icp_slam.pdf | icp_slam.pdf}} (homework instructions), \\ {{ :courses:aro:tutorials:icp_slam.zip | icp_slam.zip}} (source codes) | | 4 | 12.3./14.3. 2019 | Rado | Planning and exploration | {{ :courses:aro:tutorials:04_exploration.pdf | slides}} {{ :courses:aro:tutorials:04_homework.pdf | homework}} {{courses:aro:tutorials:hw_lab_04_src.zip | template source files}} | | 5 | 19.3./21.3. 2019 | Ondra | Waypoint navigation + TurtleBot intro + semestral work assignment| {{courses:aro:tutorials:robot_coordination.tar.gz | robot_coordination_v3.tar.gz}}| | 6 | 26.3./27.3. 2019 | Vojta | Deep Learning I (PyTorch) | {{ https://cw.fel.cvut.cz/wiki/_media/courses/aro/tutorials/deeplearning.pdf | slides }} \\ {{ https://cw.fel.cvut.cz/wiki/_media/courses/aro/tutorials/scripts.zip | scripts}} \\ {{ https://drive.google.com/file/d/1AOmYLxFYs8JO5ldGm4V0VAeM53X18ZZw/view?usp=sharing | pretrained_weights}} \\ {{ https://drive.google.com/file/d/1T0c6yhEYWKLiWBqRExRfbLQXNrEzQLpE/view?usp=sharing | training_dataset }} \\ {{ https://drive.google.com/file/d/1J9UkZMLLbSHGDE5IOWnS1IRSHcOjYI8i/view?usp=sharing | validation_dataset}} | | 7 | 2.4./4.4. 2019 | Vojta | Deep Learning II (Object detection) | {{ https://cw.fel.cvut.cz/wiki/_media/courses/aro/tutorials/barbie_detection.zip | ws package }} \\ {{ https://cw.fel.cvut.cz/b182/_media/courses/aro/tutorials/how_to_use_bagfile.pdf | 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| |