Učni načrt predmeta

Predmet:

Inteligentni sistemi vodenja robotov

Course:

Intelligent Robot Control

Študijski program in stopnja / Study programme and level	Študijska smer / Study field	Letnik / Academic year	Semester / Semester
Informacijske in komunikacijske	Inteligentni sistemi in robo	tika 1	1
Information and Communication	Intelligent Sytems and Robot	ics 1	1

Vrsta predmeta / Course type

Izbirni

Univerzitetna koda predmeta / University course code:

IKT3-628

Predavanja Lectures	Seminar Seminar	Vaje Tutorial	Klinične vaje work	Druge oblike študija	Samost. delo Individ. work	ECTS
15	15			15	105	5

*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. Tadej Petrič

Sodelavci / Lecturers:

Jeziki / Languages:

Predavanja / Lectures:

Slovenščina, angleščina / Slovenian, English

Vaje / Tutorial:

Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:

Prerequisites:

Zaključena druga stopnja bolonjskega študija ali diploma univerzitetnega študijskega programa. Potrebna so osnovna znanja iz matematike, fizike in vodenja dinamičnih sistemov. Potrebno je poznavanje osnov robotike (kinematika, dinamika).

Completed Bologna second cycle study program or an equivalent pre-Bologna university study program. Basic knowledge of mathematics, physics and control of dynamic systems is also required. Knowledge of robot systems (kinematics and dynamics) is also necessary.

Vsebina:

Content (Syllabus outline):

Uvod:
kinematika in dinamika robotskih mehanizmov, načrtovanje gibanja, vodenje robotov v sklepih in vodenje robotov v prostoru naloge

Modeliranje in simulacija robotskih mehanizmov:
simulacija robotskih sistemov v okolju MATLAB / Simulink, načrtovanje vodenja z uporabo simulacije, sprotna simulacija

Vodenje robotskih mehanizmov:
dinamična manipualcija z uporabo senzorjev sile, vida in dotika, vodenje robotov z uporabo variabilne podajnosti, optimalno vodenje robotov

Redundantni robotski sistemi:
dekompozicija naloge, reševanje redundantnosti izogibanje oviram

Sodelovanje robotov:
kinematika in dinamika dvoročnih robotov, vodenje dvoročnih robotov

Praktično usposabljanje:
praktična uporaba izbranih metod vodenja na robotih

Introduction:
kinematics and dynamics of robot mechanisms, motion planning, joint space robot control and task space robot control

Modeling and simulation of robot mechanisms:
simulation of robot manipulators in MATLAB/Simulink environment, simulation in robot control system design, real-time simulation

Robot control systems:
dynamic manipulation using force, vision and tactile sensors, variable compliance robot control, optimal robot control

Redundant robot systems:
task decomposition, redundancy resolution, obstacle avoidance

Robot cooperation:
Kinematics and dynamics of dual-arm robots, control of dual-arm robots

Practical training:
practical use of selected control techniques on robot systems

Temeljna literatura in viri / Readings:

Izbrana poglavja iz naslednjih knjig: / Selected chapters from the following books:
- M. Mihelj, T. Bajd, A. Ude, J. Lenarčič, A. Stanovnik, M. Munih, J. Rejc, S. Šlajpah. Robotics, Springer Cham, 2019, ISBN: 978-3-319-72910-7.
- B. Siciliano, L. Sciavicco, L. Villani, and G. Oriolo, Robotics: Modelling, Planning and Control, Springer-Verlag, London, UK, 2009, ISBN: 978-1-84628-641-4.
- B. Siciliano, and O. Khatib (Eds.), Springer Handbook of Robotics, Springer-Verlag Berlin Heidelberg 2008, ISBN: 978-3-540-23957-4.
- J. Hwangbo, et al. "Learning agile and dynamic motor skills for legged robots." Science Robotics 4.26 (2019): eaau5872.
- C. Laschi, B. Mazzolai, & M. Cianchetti, (2016). Soft robotics: Technologies and systems pushing the boundaries of robot abilities. Science robotics, 1(1), eaah3690.
- T. Hatanaka, N. Chopra, M. Fujita & M. W. Spong, W. (2015). Passivity-based control and estimation in networked robotics. Switzerland: Springer. ISBN: 978-3-319-15171-7
- G. Carbone F. Gomez-Bravo (Editors), Motion and operation planning of robotic systems: background and practical approaches, (Mechanisms and machine science, 29). Springer, 2015, ISBN: 978-3-319-14704-8

Cilji in kompetence:

Objectives and competences:

Cilj predmeta je osvojiti teoretična in praktična znanja iz robotske kinematike in dinamike, simulacije in vodenja robotov, učenja robotov in uporabe robotov. Poudarek je na sodobnih robotskih sistemih, kot so redundantni mehanizmi, dvoročni robotski mehanizmi in senzorsko podprto vodenje.

Študenti bodo pridobili kompetence na področju poznavanja sodobnih raziskovalno-razvojnih dosežkov in trendov na področju inteligentnih robotskih sistemov, zmožnost razvoja in uporabe specifičnih robotskih tehnologij, zmožnost izdelave aplikacij z orodji sodobnih robotskih sistemov in sposobnost načrtovati vodenja robotskih sistemov.

The objective of this course is to gain theoretical and practical knowledge of robot kinematics, dynamics, motion planning and robot applications. The emphasis is on modern robot systems like redundant mechanisms, dual-arm robot manipulators and sensor based control.

The aims of the course are to evolve competences to understand R&D achievements and trends in the fields of intelligent robot systems, to be able to develop and use specific robot technologies, be able to create applications using modern robot systems and to design robot control systems.

Predvideni študijski rezultati:

Intendeded learning outcomes:

Študent, ki bo uspešno končal ta predmet, bo pridobil znanja in razumel zgradbo kompleksnih robotskih sistemov, sisteme vodenja robotov in senzorsko podprto vodenje.

Predmet pripravlja študente, da bodo sposobni uporabljati in načrtovati različne načine vodenja robotskih sistemov, načrtovati kompleksne robotske naloge in bodo pridobili znanje uporabe informacijskih tehnologij na področju robotike.

A student who completes this course successfully will know and understand structure of complex robot systems, robot control systems and sensor based control.

This course prepares the students to be able to use and to design complex robot control systems, to plan complex robot tasks, and use of information technology in the field of robotics.

Metode poučevanja in učenja:

Learning and teaching methods:

Predavanja, seminar, konzultacije in seminarska naloga

Lectures, seminar, consultancy and seminar work

Načini ocenjevanja:

Delež v % / Weight in %

Assesment:

Pisni ali ustni izpit

Written or oral exam

Seminarska naloga

Seminar work

Ustni zagovor

Oral defence

Reference nosilca / Lecturer's references:

1.	Tadej Petrič, Leon Žlajpah, "Kinematic model calibration of a collaborative redundant robot using a closed kinematic chain", Scientific reports, 2023, vol. 13, str. 17804-1-17804 -12, ISSN 2045-2322, DOI: 10.1038/s41598-023-45156-6.
2.	Tilen Brecelj, Tadej Petrič, "Stable heteroclinic channel networks for physical human–humanoid robot collaboration", Sensors, 2023, vol. 23, no. 3, str. 1396-1-1396-18, ISSN 1424-8220, DOI: 10.3390/s23031396.
3.	Branko Lukić, Kosta Jovanović, Leon Žlajpah, Tadej Petrič, "Online cartesian compliance shaping of redundant robots in assembly tasks", Machines, 2023, vol. 11, no. 1, [article no.] 35, str. 1-14, ISSN 2075-1702, https://www.mdpi.com/2075-1702/11/1/35, DOI: 10.3390/machines11010035.
4.	Leon Žlajpah, Tadej Petrič, "Kinematic calibration for collaborative robots on a mobile platform using motion capture system", Robotics and computer-integrated manufacturing, 2022, vol. 79, str. 102446-1-102446-15, ISSN 0736-5845, DOI: 10.1016/j.rcim.2022.102446.
5.	Tadej Petrič, "Phase-synchronized learning of periodic compliant movement primitives (P-CMPs)", Frontiers in neurorobotics, 2020, vol. 14, str. 599889-1-599889-12, ISSN 1662-5218, DOI: 10.3389/fnbot.2020.599889