Subject description - B4M36UIR

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B4M36UIR Artificial Intelligence in Robotics Extent of teaching:2+2c
Guarantors:Faigl J. Roles:PO Language of
teaching:
CS
Teachers:Bošanský B., Faigl J., Lisý V. Completion:Z,ZK
Responsible Department:13136 Credits:6 Semester:Z,L

Anotation:

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.

Course outlines:

- 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

Exercises outline:

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

Literature:

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 )

Requirements:

Webpage:

https://cw.fel.cvut.cz/wiki/courses/b4m36uir

Subject is included into these academic programs:

Program Branch Role Recommended semester
MPOI7_2016 Artificial Intelligence PO 3
MPOI7_2018 Artificial Intelligence PO 3


Page updated 24.9.2018 17:49:48, semester: Z,L/2020-1, L/2017-8, L/2019-20, Z,L/2018-9, Z/2019-20, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)