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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2019/2020

Artificial Intelligence in Robotics

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Code Completion Credits Range Language
B4M36UIR Z,ZK 6 2P+2C Czech
The course cannot be taken simultaneously with:
Artificial intelligence in robotics (BE4M36UIR)
Lecturer:
Jan Faigl (guarantor), Tomáš Krajník (guarantor), Pavel Rytíř
Tutor:
Jan Faigl (guarantor), Tomáš Krajník (guarantor), Miloš Prágr, Pavel Rytíř
Supervisor:
Department of Computer Science
Synopsis:

The aim of the course is to acquaint students with the use planning approaches and decision-making techniques of artificial intelligence for solving problems arising in autonomous robotic systems. Students in the course will use the knowledge of planning algorithms, game theory, solving optimization problems and multi-agent negotiation in selected application scenarios of mobile robotics. Students first learn the basic architectures of autonomous systems based on reactive and behavioral models of autonomous systems. The considered application scenarios and robotic problems includes: path planning, persistent environmental monitoring, robotic exploration of unknown environments, online real-time decision-making, deconfliction in autonomous systems and solutions of antagonistic conflicts. In laboratory exercises, students will practice their problem formulations of robotic challenges and practical solutions in a realistic robotic simulator or using consumer mobile robots.

Requirements:
Syllabus of lectures:

- Computational models of autonomous systems

- Path planning, randomized search techniques, multi-goal path planning, and informative path planning

- Robotic exploration, online decision-making, persistent environmental monitoring, decision-making with limited resources

- Methods of game theory and safety games in mobile robotics tasks, solving antagonistic conflict

- Reactive and behavioral models in tasks of collective robotics

- Coordination and cooperation in autonomous systems

Syllabus of tutorials:

In laboratory exercises, students will practice their problem formulations of robotic challenges and practical solutions in a realistic robotic simulator or with consumer mobile robots.

- Computational models of autonomous systems

- Path planning, randomized search techniques, multi-goal path planning, and informative path planning

- Robotic exploration, online decision-making, persistent environmental monitoring, decision-making with limited resources

- Methods of game theory and safety games in mobile robotics tasks, solving antagonistic conflict

- Reactive and behavioral models in tasks of collective robotics

- Coordination and cooperation in autonomous systems

Study Objective:
Study materials:

1st chapter: Robin R. Murphy: Introduction to AI Robotics, MIT Press, Cambridge, MA, 2001

Steven M. LaValle: Planning Algorithms, Cambridge University Press, 2006 (http://planning.cs.uiuc.edu )

Note:
Further information:
https://cw.fel.cvut.cz/wiki/courses/b4m36uir
Time-table for winter semester 2019/2020:
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
roomKN:E-126
Faigl J.
Krajník T.

09:15–10:45
(lecture parallel1)
Karlovo nám.
Trnkova posluchárna K5
roomKN:E-307
Prágr M.
14:30–16:00
(lecture parallel1
parallel nr.101)

Karlovo nám.
HW-lab K307
roomKN:E-307
Prágr M.
16:15–17:45
(lecture parallel1
parallel nr.102)

Karlovo nám.
HW-lab K307
Tue
Fri
Thu
Fri
Time-table for summer semester 2019/2020:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2019-10-16
For updated information see http://bilakniha.cvut.cz/en/predmet4701506.html