Učni načrt predmeta

Predmet:
Izbrana poglavja iz robotike
Course:
Selected Topics in Robotics
Študijski program in stopnja /
Study programme and level
Študijska smer /
Study field
Letnik /
Academic year
Semester /
Semester
Informacijske in komunikacijske tehnologije, 2. stopnja Inteligentni sistemi in robotika 1 2
Information and Communication Technologies, 2nd cycle Intelligent Systems and Robotics 1 2
Vrsta predmeta / Course type
Izbirni / Elective
Univerzitetna koda predmeta / University course code:
IKT2-617
Predavanja
Lectures
Seminar
Seminar
Vaje
Tutorial
Klinične vaje
work
Druge oblike
študija
Samost. delo
Individ. work
ECTS
30 30 30 210 10

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:
izr. prof. dr. Aleš Ude
Sodelavci / Lecturers:
Jeziki / Languages:
Predavanja / Lectures:
slovenščina, angleščina / Slovenian, English
Vaje / Tutorial:
Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:
Prerequisites:

Zaključen študijski program prve stopnje s področja naravoslovja, tehnike ali računalništva.

Student must complete first-cycle study programmes in natural sciences, technical disciplines or computer science.

Vsebina:
Content (Syllabus outline):

1) Uvod
V uvodnem delu predmeta se bodo študentje seznanili z vpeljevanjem robotov v industrijo in druge dejavnosti v svetu in specifično v Sloveniji, fleksibilna avtomatizacija v industriji.

2) Direktna kinematika robota
primer direktne kinematike planarnega mehanizma, izpeljava kinematičnih enačb, sistem trigonometričnih enačb, rotacijska matrika, vektorski parametri mehanizma, sinteza kinematičnih enačb za splošni serijski mehanizem.

3) Inverzna kinematika robota
primer inverzne kinematike planarnega mehanizma, problem nerealnih rešitev, problem več realnih rešitev, kinematične enačbe v Jacobijevi obliki, numerično reševanje inverzne kinematike z Newton-Raphsonovo metodo.

4) Dinamični model robota
pomen dinamičnega modela, Lagrangeove dinamične enačbe, obravnava enostavnega primera, splošni dinamični model robotskega mehanizma.

5) Načrtovanje robotskih mehanizmov obravnava matematičnih kriterijev za optimalno sintezo robotskega mehanizma, volumen in oblika delovnega prostora, kinematična prilagodljivost, manipulabilnost.

6) Paralelni roboti
primeri paralelnih robotov, posebnosti direktne in inverzne kinematike, prednosti in slabosti uporabe paralelnih robotov.

7) Redundantni roboti
primeri kinematične redundance, osnovni principi obravnave redundantnih robotov, pomen kinematične redundance pri načrtovanju in vodenju robotov, primer humanoidne manipulacije

1) Introduction
Introduction to robotics, robotics in the world and specifically in Slovenia, advantages of flexible automation in industry.

2) Direct kinematics of robots
Example of direct kinematics of a planar mechanism, development of kinematic equations, system of trigonometric equations, rotation matrix, vector parameters of mechanisms, synthesis of kinematic equations for general serial mechanisms.

3) Inverse kinematics of robots
Example of inverse kinematics of a planar mechanism, problem of imaginary solutions, problem of multiple solutions, kinematic equations in Jacobian form, Jacobian matrix, inverse kinematics computed by Newton-Raphson numerical method.

4) Robot dynamic model
Role of dynamic models in robotics, Lagrange dynamic equations, simple examples, general form of a dynamic model

5) Design od robot mechanisms
Mathematical criteria for optimum robot design, workspace volume and workspace form, compactness of robot workspace, kinematic flexibility, manipulability and kinematic index

6) Parallel robots
Examples of parallel robots, characteristics of inverse and direct kinematics computation, advantages and disadvantages of parallel robots relative to robots which posses serial mechanisms.

7) Redundant robots
Examples of kinematic redundancy, basic principles of treating redundant robots, the role of kinematic redundancy in design and control of robot manipulators, examples of humanoid manipulation, human arm as a redundant mechanism in a majority of tasks.

Temeljna literatura in viri / Readings:

- J. Lenarčič, T. Bajd, Robotski mehanizmi, Ljubljana : Fakulteta za elektrotehniko, 2003
- J. J. Craig, Introduction to Robotics (Mechanics and Control), Pearson; 3 edition, 2004
- L. Sciavicco, B. Siciliano, Modelling and Control of Robot Manipulators, CreateSpace Independent Publishing Platform; 2nd edition, 2001

Cilji in kompetence:
Objectives and competences:

Cilj predmeta je posredovati temeljno znanje o mehanizmih robotskih manipulatorjev, ki obsega predvsem tematike o gibanju robotov, analizi mehanizmov in njihovem načrtovanju. Predmet obravnava kinematiko in dinamiko robotskih mehanizmov za potrebe razumevanja, vodenja in programiranja njihovega gibanja.
V prvem delu predmeta se študentje spoznajo z direktno in inverzno kinematiko, z obravnavo primerov se seznanijo s posebnostmi analitičnega in numeričnega preračunavanja kinematike serijskih mehanizmov.
V drugem delu predmet obravnava dinamiko serijskih mehanizmov in postopek izpeljave dinamičnega modela.
V nadaljevanju so predstavljeni pristopi pri načrtovanju najboljših robotskih mehanizmov glede na potrebe, ki izhajajo iz predvidenih opravil.
Na koncu predmeta se študentje spoznajo z nekonvencionalnimi robotskimi mehanizmi, kot so paralelni mehanizmi in redundantni mehanizmi.

The goal of the course is to present a basic knowledge on mechanisms of robot manipulators related to their motion, as well as their analysis and synthesis. The most efficient methods of treating direct and inverse kinematics and dynamics for the purpose of understanding, control and programming of robot motion are reported.
In the first part of the course, the students learn how to model the inverse and direct kinematics of robot mechanisms and treat different cases of serial robot mechanisms.
The following topic is related to robot dynamics and the basic principles of developing dynamic models are studied.
Optimum design of robot mechanisms and different criteria relative to the requirements of robot tasks are also presented.
In the end, unconventional robot mechanisms are treated, such as redundant and parallel mechanisms.
Students learn the advantages and disadvantages of such mechanisms with respect to standard serial (industrial-type) mechanisms.

Predvideni študijski rezultati:
Intendeded learning outcomes:

Študenti bodo z uspešno opravljenimi obveznostmi tega predmeta pridobili:
- Sposobnost analize, sinteze in predvidevanja rešitev ter posledic
- Obvladanje raziskovalnih metod, postopkov in procesov, razvoj kritične in samokritične presoje
- Sposobnost uporabe znanja v praksi
- Avtonomnost v strokovnem delu
- Razvoj komunikacijskih sposobnosti in spretnosti, posebej komunikacije v mednarodnem okolju
- Etična refleksija in zavezanost profesionalni etiki
- Kooperativnost, delo v skupini (in v mednarodnem okolju)
- Poznavanje robotskih mehanizmov za namene programiranja in vodenja robotov
- Sposobnost vpeljevanja robotov v proizvodne procese
- Sposobnost ocenjevanja robotov z vidika gibalnih značilnosti in predvidenih delovnih nalog

Students successfully completing this course will acquire:
- An ability to analyse, synthesise and anticipate solutions and consequences
- To gain the mastery over research methods, procedures and processes, a development of the critical judgement
- An ability to apply the theory in to a practice
- An autonomy in the professional work
- Communicational-skills development; particularly in international environment
- Ethical reflexion and obligation to a professional ethics
- Cooperativity, team work (in international environment)
- To gain knowledge on robot mechanisms and the ability to program and control robots
- Ability to introduce robots in various working processes
- Ability to evaluate robot motion and performance characteristics for different tasks

Metode poučevanja in učenja:
Learning and teaching methods:

Predavanja, seminarji, laboratorijsko delo

Lectures, seminar work, laboratory work

Načini ocenjevanja:
Delež v % / Weight in %
Assesment:
Seminar
50
Seminar
Ustni izpit
50
Oral exam
Reference nosilca / Lecturer's references:
1. PAHIČ, Rok, GAMS, Andrej, UDE, Aleš. Reconstructing spatial aspects of motion by image-to-path deep neural networks. IEEE Robotics and automation letters. 2021, vol. 6, no. 1, str. 255-262. ISSN 2377-3766
2. MAVSAR, Matija, RIDGE, Barry, PAHIČ, Rok, MORIMOTO, Jun, UDE, Aleš. Simulation-aided handover prediction from video using recurrent image-to-motion networks. IEEE transactions on neural networks and learning systems. [Print ed.]. [in press] 2022, 13 str. ISSN 2162-237X
3. PAHIČ, Rok, LONČAREVIĆ, Zvezdan, GAMS, Andrej, UDE, Aleš. Robot skill learning in latent space of a deep autoencoder neural network. Robotics and autonomous systems. [Print ed.]. 2021, vol. 135, str. 103690-1-103690-12. ISSN 0921-8890
4. NEMEC, Bojan, YASUDA, Kenichi, UDE, Aleš. A virtual mechanism approach for exploiting functional redundancy in finishing operations. IEEE transactions on automation science and engineering. [Print ed.]. 2021, vol. 18, no. 4, str. 2048-2060. ISSN 1545-5955
5. GAŠPAR, Timotej, KOVAČ, Igor, UDE, Aleš. Optimal layout and reconfiguration of a fixturing system constructed from passive Stewart platforms. Journal of manufacturing systems. 2021, vol. 60, str. 226-238. ISSN 0278-6125