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ae3m33iro -- Intelligent robotics, summer semester 2014/2015

The subject aims

The subject will teach students the principles needed to create/use robots able to perceive and understand the surrounding world and understand it, plan the activity of robots with cognitive abilities 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 wider applicability in designing and building of intelligent machines.

Lectures: Monday 10:00-12:15, KN:E-301

Lecturer: Václav Hlaváč (VH) with the occasional help of Michala Reinštein (MR) and Karel Zimmermann (KZ).

The typical lecture will have two parts. The first part, typically a longer one lasting about 90 minutes, will provide the usual lecture. The second shorter part of the lecture (shown in the following time plan in italics) the topics will be refreshed which the student should already know and which are needed in lectures, labs or homeworks. The shorter part of three lectures is dedicated to writing three parts of the exam written test. We motivate the student to study continuously by decomposing the written test into three parts.

Week Date Studied topics Presentations
1 22.2. Robotics, motivation. Linear algebra should be refreshed as a homework. Int. robotics - anchoring, Lin. algebra, prerekvizita
2 29.2. Vector algebra of bodies in 3D. Kameras and their calibration. Homography, geometry of two cameras. Overdetermined systems of linear equations and their solution. Least squares. Geometry for robotics, Least squares, Geometry of a single camera
3 7.3. Probability as a tool. Statistical classifiers. Probability, rehearsal, Statistical pattern recognition, overview
4 14.3. Feedback. Test 1. Feedback in Cybernetics
5 21.3. Robot kinematics. Kinematika
6 28.3. No lecture. Holiday - Easter Monday
7 4.4. Robot kinematics.. Robots and their architectures. Actuators and drives. Robot control architectures, Actuators for robots
8 11.4. Trajectory of a manipulator/mobile robots. Sensors Traj. generation 1, Traj. generation 2, Sensors for robots
9 18.4. Robot world and its representation. Test 2. Robot world representation
10 25.4. Robotic path planning. Reminder of problem solving from artificial intelligence. Planning in robotics
11 2.5. Linear and extended Kalman filter matlam_mars_landerintro_data_fusion bayes-ekf
12 9.5. SLAM
13 16.5. K. Zimmermann. Epipolar geometry, its use in depth sensors. Test 3.
14 23.5. Tactile feedback in robotics. Manipulation tasks. Grippers.

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

On hold

Labs and exercises

Instructors: Ing. Karel Zimmermann, Ph.D. (head), Ing. Vladimír Kubelka, Mgr. Martin Pecka.

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.


The English translation is pending.

  • Three tests will be written at the lecture. The test will last for about 30 minuts.
  • Test 1 (14. 3. 2016, the scope fixed on 7. 3. 2016)
    • Robot definitions. Parts of robots. Locomotion/manipulation in robotics.
    • Automation of the factory production. Milestones in the increase of labor productivity. Where do robot fit in production?
    • Representation of a body in 3D space. Expressing translation and rotation. Rotational matrix. Euler and Cardan angles. Composing rotations.
    • Coordinates transformations in homogeneous cooordinates.
    • Overdetermined system of linear equations. Least squares method.
    • Geometry of a single camera. Projective mapping. Outer and inner camera calibration parameters. How is geometric calibration performed? Homography and its use in computer vision.
    • Fundamentals of probability. Differnce between probability theory and statistics. Random variable, statistical independence, conditional probability. Bayes formula and its use. Distribution function, probability density function. Random vector and its characterization. Bayesian risk in decision making. Classification.
  • Test 2 (18. 4. 2016)
    • Concept of degrees of freedom (in mechanical system).
    • Types of kinematic pairs. Structures of manipulators.
    • Coordinates transformation.
    • Direct and inverse kinematic task.
    • Aplying robots with the emphaisis to intelligent robots. Examples of applying robots.
    • Feedback. General principles. Example of J. Watt's governor. Basic control and involved dynamic troubles.
    • Position and speed servomechanism. Importance of the feedback loop when suppressing uncertainty in real applications.
    • Basic principles of cybernetics. Overview of the history of cybernetics, its key personalities.
    • Robot architectures, deliberative, reactive, subsumption architecture and hybrid one. Hybrid architecture (basic explanation expected).
    • Robot control principles. Robot control as examples, e.g. examples coverign vacuum cleaner, welding robot, robot in assembly.
    • Practical example based on physical and technological principles learn in previous subjects. The scope can be estimated from discussions at lectures.
    • Drives - electric, hydraulic, pneumatic, their properties and where are commonly used.
    • Robot sensoers. Taxonomy. Basic principles, examples.
    • Sensors for odometry. Gyroscope and its principle. GPS, differential GPS.
    • Manipulator trajectory. Its mathematical expression from the approximation point of view. Approximation by polynomials.
  • Test 3 (16. 5. 2016)
    • Robot path planning.
    • Robot world representation. Occupancy grid. Metric and topological map. A more abstract graph representation.
    • Map (of a robot), its creation and refereshment.
    • SLAM..
    • A force compliant robot.
    • Tactile sensors. Information processing in robotics. Tactile feedback in robotics. Examples.
  • Replacement test (23. 5. 2016 v 12:45 hodin v KN:G-205). Test is intended for students, who could not write the regular tests for serious reasons. The replacement test will cover topics taught in the whole semester. I will ask the student at the spot why she/he did not write the regular test. Není potřebné se z neúčasti na řádných testech omlouvat. The replacement test can substitute only one missing test.

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

  • IEEE Transactions on Intelligent Transportation Systems
  • IEEE/ASME Transactions on Mechatronics
  • IEEE Transactions on Robotics
  • Autonomous Robots Journal
  • International Journal of Robotics Research
  • Robotics and Autonomous Systems

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 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, March 7, 2016

courses/ae3m33iro/start.txt · Last modified: 2016/05/18 07:55 by hlavac