PristupačnostMulti-robot Systems
Data is displayed for academic year: 2023./2024.
Lectures
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
- Student is able to recognize and describe basic concepts, principles and theory related to multi-robot systems
- Student understands, could interpret, could compare and could analyse information that is based on knowladge of multi-agent systems.
- Student is able to implement knowledge on multi-agent systems in novel situations in order to resolve problems.
- Student is able to categorize problems in multi-agent systems and understand their organizational structure
- 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
In-person lectures.
LaboratoryStudents' project.
Week by Week Schedule
- Mission planning
- Mission scheduling
- Centralized vs decentralized coordination
- Leader-follower
- Potential field based formation
- Consensus based formation
- Trust-based consensus
- Midterm exam
- Binary consenus
- Types of random walk
- Behavior analysis
- Reynolds based swarm
- Load transport
- Search and rescue
- Final exam
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 223734
Winter semester
5 ECTS
L3 English Level
L1 e-Learning
30 Lectures
0 Seminar
0 Exercises
8 Laboratory exercises
0 Project laboratory
0 Physical education excercises
Grading System
Excellent
Very Good
Good
Sufficient