University of West Attica
Artificial Intelligence and Data Science
Course info:
Semester: 7
Elective
ECTS: 6
Hours per week: 2
Professor: T.B.D.
Teaching style: Face to face, distance learning
Grading: Individual assignments, Team project, Written essay in teams with oral presentation.
| Activity | Workload |
|---|---|
| Lectures | 26 |
| Team work | 58 |
| Independent study | 66 |
| Course total | 150 |
Learning Results
Upon successfully completing this course, student will be able to:
- Understand, design and critically appraise navigation, guidance and communication for autonomous systems
- Implement navigation, guidance and communication for autonomous systems.
- Implement filters in order to localize moving objects whose locations are subject to noise.
- Implement search algorithms to plan the shortest path from one point to another subject to costs on different types of movement.
- Implement controls to smoothly correct an autonomous robot.
Skills acquired
- Work individually and in teams
- Advance free, creative and causative thinking
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Introduction to autonomous mobile systems
- Locomotion
- Mobile robot kinematics
- Perception
- Mobile robot localization
- Planning and navigation
- J. Craig, Introduction to Robotics: Mechanics and Control, 4th edition, Pearson, 2018.
- M. Mataric, The Robotics Primer (Intelligent Robotics and Autonomous Agents series), MIT Press, 2007.
- B. Siciliano, L. Sciavicco, L. Villani, G. Oriolo, Robotics: Modelling, Planning and Control, Springer-Verlag London 2009.
- H. Asada, J. Slotine, Robot analysis and Control, John Wiley & Sons, 1986.
- R. Siegwart, I. Nourbakhsh, Introduction to Autonomous Mobile Robots, MIT Press, 2004.
- Learning Results - Skills acquired
-
Learning Results
Upon successfully completing this course, student will be able to:
- Understand, design and critically appraise navigation, guidance and communication for autonomous systems
- Implement navigation, guidance and communication for autonomous systems.
- Implement filters in order to localize moving objects whose locations are subject to noise.
- Implement search algorithms to plan the shortest path from one point to another subject to costs on different types of movement.
- Implement controls to smoothly correct an autonomous robot.
Skills acquired
- Work individually and in teams
- Advance free, creative and causative thinking
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Course content
-
- Introduction to autonomous mobile systems
- Locomotion
- Mobile robot kinematics
- Perception
- Mobile robot localization
- Planning and navigation
- Recommended bibliography
-
- J. Craig, Introduction to Robotics: Mechanics and Control, 4th edition, Pearson, 2018.
- M. Mataric, The Robotics Primer (Intelligent Robotics and Autonomous Agents series), MIT Press, 2007.
- B. Siciliano, L. Sciavicco, L. Villani, G. Oriolo, Robotics: Modelling, Planning and Control, Springer-Verlag London 2009.
- H. Asada, J. Slotine, Robot analysis and Control, John Wiley & Sons, 1986.
- R. Siegwart, I. Nourbakhsh, Introduction to Autonomous Mobile Robots, MIT Press, 2004.