Intellligent Robotic Systems

Course Information
TitleΕυφυή Ρομποτικά Συστήματα / Intellligent Robotic Systems
CodeUAV03
FacultyEngineering
SchoolElectrical and Computer Engineering
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter/Spring
CoordinatorAndreas Symeonidis
CommonNo
StatusActive
Course ID600024548

Programme of Study: DPMS Enaéria Aytónoma Systīmata

Registered students: 9
OrientationAttendance TypeSemesterYearECTS
KORMOSCompulsory Course115
Class Information
Academic Year2025 – 2026
Class PeriodWinter
Faculty Instructors
Class ID
600290472
Course Type 2021
Specialization / Direction
Course Type 2016-2020
  • Scientific Area
  • Skills Development
Course Type 2011-2015
Knowledge Deepening / Consolidation
Mode of Delivery
  • Face to face
  • Distance learning
Digital Course Content
Language of Instruction
  • Greek (Instruction)
  • English (Instruction, Examination)
Prerequisites
General Prerequisites
Basic knowledge of data structures, probability theory, geometry, programming
Learning Outcomes
Upon successful completion of the course, students will be able to: - know the basic types of sensors used in aerial and non-robotic systems - identify the basic types of motors/drive models used in aerial and non-robotic systems - know the basic types of path construction, mapping, positioning, exploration and coverage for aerial and non-autonomous vehicles - design the architecture and functionality of a robotic system based on specifications - define the communication strategy of a robot team
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
The aim of the course is to learn the concept and the operation of autonomous systems. First, an introduction to the concept of autonomy and behaviours is given, as well as to the ways of representing them (Stimulus-Response diagrams, FSAs, etc.), to the ways of encoding and combining them (Motor Schema / Subsumption). Then, the structure and the way of creating the basic autonomy architectures are discussed. Next, the algorithms that make autonomy of a robotic vehicle possible are discussed. These include mapping and localization (SLAM), path planning, autonomous coverage and exploration, as well as multiple robotic system techniques.
Keywords
Autonomy, behaviors, architectures, mapping, localization, path planning, exploration, multiple robots
Educational Material Types
  • Notes
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Description
● Lectures will be delivered in the form of presentations, which will include multimedia (videos and/or animations), which aim at an optimal understanding of the concepts. In addition, subject-related algorithms will be run during the lectures in simulated environments. Regarding the communication with students, a default platform (e.g. Discord) will be defined, where both asynchronous and more direct communication with the lecturer and communication between students will be achieved. Finally, the assessment of the course will be carried out through the eLearning platform.
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures682.7✓✓
Written assigments572.3✓
Total1255
Student Assessment
Student Assessment methods
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Assignment (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
- Autonomous Mobile Robots and Multi-Robot Systems [electronic resource]Κωδικός Βιβλίου στον Εύδοξο: 91714246 - ΠΙΘΑΝΟΤΙΚΗ ΡΟΜΠΟΤΙΚΗ Κωδικός Βιβλίου στον Εύδοξο: 12858802
Last Update
08-11-2024