Učni načrt predmeta

Predmet:

Humanoidna in servisna robotika

Course:

Humanoid and Service Robotics

Študijski program in stopnja / Study programme and level	Študijska smer / Study field	Letnik / Academic year	Semester / Semester
Informacijske in komunikacijske tehnologije, 3. stopnja	Inteligentni sistemi in robotika	1	1
Information and Communication Technologies, 3rd cycle	Intelligent Systems and Robotics	1	1

Vrsta predmeta / Course type

Izbirni / Elective

Univerzitetna koda predmeta / University course code:

IKT3-623

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. Bojan Nemec

Sodelavci / Lecturers:

Jeziki / Languages:

Predavanja / Lectures:

Slovenščina, angleščina / Slovenian, English

Vaje / Tutorial:

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

Prerequisits:

Vsebina:

Content (Syllabus outline):

Osnovne značilnosti humanoidnih in servisnih robotov

Predstavitev nalog v parametrični obliki:
- Diskretne in periodične naloge, 
- Predstavitve s skritimi markovskimi modeli, skupek Gaussovih porazdelitev, mešana Gaussova regresija, dinamični generatorji giba, verjetnostni generatorji giba, interaktivni generatorji giba, podajni generatorji giba.

Učenje robotov:- 
- s posnemanjem
- spodbujevano učenje

Posploševanje gibanja:
- Statistične metode posploševanja

Avtonomno prilagajanje gibanja:
- z uporabo učečih regulatorjev
- z uporabo spodbujevanega učenja
- z uporabo nevronskih mrež

Učenje in prilagajanje robotskih nalog v latentnih prostorih:
- zapis nalog v latentnih prostorih
- učenje in izvajanje gibanja v latentnih prostorih

Optimalno vodenje robotov:
- optimalni regulator za linearne sisteme 
- razširitev optimalnega vodenja za nelinearne sisteme
- prediktivno vodenje s pomočjo modelov

Humanoidni in servisni roboti v človekovem okolju:  
- sodelovanje človeka z robotom
- fizična interakcija človek – robot in robot – okolje
- sinhronizacija gibanja

Dvoročna manipulacija:
- pristop gospodar–suženj
- pristop s simetrično dekompozicijo nalog

Lokomocija

Navigacija:
- SLAM
- navigacija v zaprtih prostorih
- navigacija na prostem

Senzorski sistemi za zaznavo okolja:
- RGBD kamere
- laserski detektorji
- detektorji bližine

Uporaba servisnih robotov

Basic structure of humanoid and service robots

Parametric policy representation
- Discrete and periodic policies, 
- Representations using Hidden Markov model, Gaussian mixture model, Gaussian mixture regression, Dynamic motion primitives, Probability motion primitives, Interactive motion primitives, Compliant motion primitives

Learning for humanoid and service robots:
- Imitation learning
- Reinforcement learning

Motion generalization:
- Statistical generalization methods

Autonomous motion adaptation:
- Using iterative learning control
- Using reinforcement learning
- Using neural networks

Robot learning and adaptation in latent spaces
- Latent space policy representation
- Learning and task execution in latent spaces

Optimal robot control
- Using linear quadratic regulator
- Extension to non-linear robot dynamics
- Model predictive control in robotics

Humanoid and service robots in human environments: 
- Human – robot cooperation
- Physical human – robot and robot – environment interaction
- Motion synchronization and adaptation

Bimanual robot control
- Master-slave approach
- Symmetrical task decomposition

Locomotion

Navigation:
- SLAM
- Indoor navigation
- Outdoor navigation

Advanced sensory systems for environment detection and localization:
- RGBD cameras
- Laser scanners
- Proximity sensors

Service robot applications

Temeljna literatura in viri / Readings:

Izbrana poglavja iz naslednjih knjig: / Selected chapters from the following books:
- Siciliano, B., and Khatib, O. (eds.) Springer Handbook of Robotics, Springer-Verlag Berlin Heidelberg, 2016. ISBN 978-3-319-32552-1
- Corke, P. Field and Service Robotics, Springer, 2006. ISBN 10 3-540-33452-1
- Calinon, S. Robot Programming by Demonstration, EPFL Press 2009, ISBN-13: 978-1439808672
- Vadakkepat, P. and Goswami, A. (eds.) Humanoid Robotics: A Reference, Springer, 2017, ISBN 978-94-007-6045-5
- Haddadin, S.: Towards Safe Robots, Springer Berlin Heidelberg, 2014
- Kober, J. and Peters, J. Learning Motor Skills from Algorithms to Robot Experiments. Heidelberg: Springer-Verlag, 2014. ISBN 978-3-319-03193-4
- Nemec, B., and Ude, A. Robot skill acquisition by demonstration and explorative learning, In New Trends in Medical and Service Robotics, Springer 2014, ISBN 978-3-319-05431-8
- Calinon, S. A Tutorial on Task-Parameterized Movement Learning and Retrieval, Intelligent Service Robotics (Springer), 9:1, 1-29, 2016.
- Herzog, A., Rotella, N., Mason, S., Grimminger, S., Schaal, S., Righetti, L. Momentum control with hierarchical inverse dynamics on a torque-controlled humanoid, Autonomous Robot 40: 473, 2016.
- Chen, N., Karl, M., van der Smagt, P. Dynamic Movement Primitives in Latent Space of Time-Dependent Variational Autoencoders. Proc. 16th IEEE-RAS International Conference on Humanoid Robots, 2016.

Cilji in kompetence:

Objectives and competences:

Predvideni študijski rezultati:

Intendeded learning outcomes:

Metode poučevanja in učenja:

Learning and teaching methods:

Načini ocenjevanja:

Delež v % / Weight in %

Assesment:

Ustni izpit

50 %

Oral exam

Seminarska naloga

25 %

Seminar work

Ustni zagovor

25 %

Oral defense

Reference nosilca / Lecturer's references:

1.	A. Gams, B. Nemec, A. J. Ijspeert, A. Ude. Coupling movement primitives : interaction with the environment and bimanual tasks. IEEE transactions on robotics, 30 (49), 816-830, 2014
2.	R. Vuga, B. Nemec, A. Ude. Speed adaptation for self-improvement of skills learned from user demonstrations. Robotica, 34 (12), 2806-2822, 2016.
3.	A. Gams, T. Petrič, M. Do, B. Nemec, J. Morimoto, T. Asfour, A. Ude. Adaptation and coaching of periodic motion primitives through physical and visual interaction. Robotics and autonomous systems, 75,340-351, 2016.
4.	F. Abu Dakka, B. Nemec, J. Jørgensen, T. R. Savarimuthu, N. Krüger, A. Ude. Adaptation of manipulation skills in physical contact with the environment to reference force profiles. Autonomous robots, 39 (2), 199-217, 2016.
5.	M. Deniša, A. Gams, A. Ude, T. Petrič. Learning compliant movement primitives through demonstration and statistical generalization. IEEE/ASME transactions on mechatronics, 21 (5), 2581-2594, 2016.