Multi-robot Systems

Data is displayed for academic year: 2023./2024.

Associate Lecturers

Laboratory exercises

Course Description

Modeling of multi-robot systems in order to analyze behavior and to design control algorithms. Mission planning and scheduling in multi-robot systems. Formation control in multi-robot systems. Synthesis of decision making algorithms in multi-robot systems.

Study Programmes

University graduate
[FER3-EN] Control Systems and Robotics - profile
(3. semester)

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


In-person lectures.


Students' project.

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


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

For students


ID 223734
  Winter semester
L3 English Level
L1 e-Learning
30 Lectures
0 Seminar
0 Exercises
8 Laboratory exercises
0 Project laboratory

Grading System

Very Good