Multi-robot Systems

Learning Outcomes

  1. Student is able to recognize and describe basic concepts, principles and theory related to multi-robot systems
  2. Student understands, could interpret, could compare and could analyse information that is based on knowladge of multi-agent systems.
  3. Student is able to implement knowledge on multi-agent systems in novel situations in order to resolve problems.
  4. Student is able to categorize problems in multi-agent systems and understand their organizational structure
  5. Student is able to connect existing ideas from the field of multi-agent systems and is able to offer novel solution

Forms of Teaching

Lectures

Laboratory

Week by Week Schedule

  1. Mission planning
  2. Mission scheduling
  3. Centralized vs decentralized coordination
  4. Leader-follower
  5. Potential field based formation
  6. Consensus based formation
  7. Trust-based consensus
  8. Midterm exam
  9. Binary consenus
  10. Types of random walk
  11. Behavior analysis
  12. Reynolds based swarm
  13. Load transport
  14. Search and rescue
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (3. semester)
Communication and Space Technologies (profile)
Free Elective Courses (3. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (3. semester)
Computer Engineering (profile)
Free Elective Courses (3. semester)
Computer Science (profile)
Free Elective Courses (3. semester)
Control Systems and Robotics (profile)
Core-elective courses 1 (3. semester)
Data Science (profile)
Free Elective Courses (3. semester)
Electrical Power Engineering (profile)
Free Elective Courses (3. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (3. semester)
Electronic and Computer Engineering (profile)
Free Elective Courses (3. semester)
Electronics (profile)
Free Elective Courses (3. semester)
Information and Communication Engineering (profile)
Free Elective Courses (3. semester)
Network Science (profile)
Free Elective Courses (3. semester)
Software Engineering and Information Systems (profile)
Free Elective Courses (3. semester)

Literature

(.), Frank L. Lewis, Kristian Hengster-Movric, Hongwei Zhang, Abhijit Dasgupta: Cooperative Control of Multi-Agent Systems: Optimal and Adaptive Design Approaches,
(.), .,

For students

General

ID 223733
  Winter semester
5 ECTS
L3 English Level
L1 e-Learning
30 Lectures
8 Laboratory exercises