Table of Contents

be3m33aro -- Autonomous robotics, summer semester 2016/2017

The subject aims

The subject will teach students the principles needed to create/use robots able to perceive the surrounding world and understand it, plan the activity of robots with in it including the possibility to modify it. Architectures of robots with cognitive abilities will be explained and their implementations demonstrated. Students will experiment in labs/exercises with robots. The studied matter has a wider applicability in designing and building of intelligent machines.

Lectures: Monday 10:00-12:15, KN:E-107

Lecturer: Václav Hlaváč (VH, default) with the occasional help of Karel Zimmermann (KZ).

The shorter part of three lectures (about 35 minutes) is dedicated to writing the exam written test in three parts. We motivate the student to study continuously by decomposing the written test.

Week Date Studied topics Presentations
1 20.2. Robotics, motivation, manipulator in industry. Kinematics, overview. Linear algebra should be refreshed as a homework. Anchoring robots Kinematics
2 27.2. Autonomous robots, architectures. Autonomus robots, architectures
3 6.3. Deliberating robot, modules/tasks, configuration space Representation for reasoning
4 13.3. KZ: Robot with a camera. Geometry of one camera. Camera calibration. Homography. pinhole.pdf
5 20.3. KZ: Depth from image and similar sensors. Use of depth maps. Least-Squares Fitting of Two 3-D Point Sets mapping.pdf
6 27.3. Trajectory of a manipulator/mobile robot and its calculation. Test 1. Trajectory generation
7 3.4. KZ: Path planning. Probabilistic methods. Random planning
8 10.4. Path planning. Deterministic methods. Deterministic planning
17.4. State holiday. Easter Monday.
9 24.4. SLAM Test 2. SLAM
10 2.5. KZ: Reinforcement learning in robotics & ROS 01_object_detection.pdf 02_reinforcement_learning.pdf 03_ros_wagner.pdf
1.5. State holiday. Labor day.
8.5. State holiday. Victory day.
11 11.5. Tactile feedback in robotics. Tactile robotics
12 15.5. Force compliant robot. Manipulation tasks. Grippers. Test 3.
13 22.5. Humanoid robots.

Presentations of V. Hlaváč's lectures are available either in English or in Czech, and sometimes in both languages.

Expected previous knowledge or hints for the subject or its labs

It is assumed that students of this course have a working knowledge of mathematical analysis, linear algebra, probability theory and statistics. In addition, basic programming skills, mainly in Matlab, are expected. This master subject should not repeat the knowledge, which was taught in the Cybernetics and Robotics study branch in bachelor studies. The subject would be too shallow otherwise.

It could happen that some students did not study the topics, which are considered a prerequisite of the subject Autonomous robotics. They have to study or refresh their knowledge on their own. Some other knowledge/skills might be useful in the subject labs.

I offer students the aid to refresh their knowledge by providing them presentations related to the topic. Most presentations were prepared by me (Václav Hlaváč), Michal Reinštein (the past instructor of the course), Karel Zimmermann and other colleagues.

Author Presentation and the link to it
V. Hlaváč Probability and statistics, rehearsal
V. Hlaváč Least squares
V. Hlaváč Geometry for robotics
V. Hlaváč Feedback, core of cybernetics
V. Hlaváč Actuators for robotics
V. Hlaváč Sensors for robotics
V. Hlaváč Robotic middleware, ROS
K. Zimmermann Visual odometry
T. Svoboda RANSAC
M. Reinštein State estimate for mobile robotics
M. Reinštein MATLAB mars lander
M. Reinštein Intro to data fusion
M. Reinštein Bayesian extended Kalman filter
K. Zimmermann Bayesian decision theory cookbook

Labs and exercises

Instructors: Ing. Karel Zimmermann, Ph.D. (head), Ing. Vladimír Kubelka, Mgr. Radoslav Škoviera, Ph.D., Ing. Libor Wagner.

The details are given in a separate section labs.

Reminder: Visiting lectures is facultative according to the Study and Exam Order of the CTU. However, it is required at the labs/exercises that student knows the matter explicated at lectures. The student may, refresh the matter from the recommended literature too.

Tests and areas of expected foreknowledge

Conditions for obtaining the credit from the subject

Work out and succesfully submitting of the assigment at lab/exercises. Writting three tests.

  1. Steven M. LaValle. Planning Algorithms, Cambridge University Press, 2006. (volně na internetu, http://planning.cs.uiuc.edu/)
  2. R. Pfeifer, C. Scheie. Understanding Intelligence, MIT Press, 2002.
  3. B. Siciliano, O. Khatib (editoři). Handbook of Robotics, Springer-Verlag, Berlin 2008.

Assesment of the student at the exam, marks

The English translation is pending.

Student's performance in labs can bring 40 points maximally.

The exam consists of the written and the oral part.

Three tests arew written in three distinct dates on the lecture. Students knowledge from theory is tested. There could be examples (to be calculated) in the test too. The scope of the test will be publishe a week before the test at latest. Each written test can yield max. 10 points. It is required that the student has to gain 10 points at least from written test to be eligible to come to the oral exam. Students who cannot attend the test due to illness (verified by the sick certificate) or for other significant reason explained in advanced to the head of exercises (he will decide if the reason is acceptable), will be asked to write the replacemet written test in the single assigned date in the last week of the semester. The replacement test will cover the material of the whole subjec.

The oral test can yield max. 30 points. Only students with the credit (zápočet) are eligible for being examined orally. The student will bring a printed scientific paper in English tackling the subject domain, which he will study in advance. The purpose of oral exam is also to verify student's deeper knowledge in the domain chosen by the student. It is also verified that the student is able to put his knowledge into the context of student's previous study. The paper should not be older than 5 years. It should be from journals as listed below

Students have access to electronic resources through the appropriate portal paid by ČVUT. Students have to know bibligraphic record matching to the paper. Conference papers are not eligible. It is prefered if the students brings her/his printed working copy with notes.

Final assesment of the subject

No of points Exam assessment
0-49 F
50- 59 E
60-69 D
70-79 C
80-89 B
90-100 A

Plagiarism

Plagiarism is unacceptable in the subject. If a student is caught copying from a colleague at a written test, she/he will be marked with zero points without the possibility to write this particular test again. The results from lab/exercises are compared with results of others. Plagiarism will be punished. The unit responsible for student affairs will be asked to mention the plagiarism attempt to the study documentation of a particular student.

A wish to students

I wish the subject students the enjoyment from intelligent robotics. I also wish their study run smoothly. I look forward to your feedback. Talk to me after the lecture in person or write me an email.

V. Hlaváč, February 3, 2017