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Course Outline
Introduction to Multi-Robot Systems
- Overview of coordination and control architectures in multi-robot setups
- Applications across industry, research, and autonomous systems
- Distinguishing between centralised and decentralised system architectures
Foundations of Swarm Intelligence
- Core principles of collective intelligence and self-organisation
- Biological inspirations: ants, bees, and bird flocks
- Emergent behaviour and system robustness in swarm contexts
Communication and Coordination Mechanisms
- Models and protocols for inter-robot communication
- Consensus algorithms and distributed agreement protocols
- Strategies for task allocation and resource sharing
Control and Formation Strategies
- Leader-follower, behaviour-based, and virtual structure control methods
- Algorithms for flocking, coverage, and pursuit–evasion
- Maintaining formation under conditions of noisy communication
Swarm Optimisation Algorithms
- Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO)
- Applications in path planning and dynamic task assignment
- Hybrid approaches that combine machine learning with swarm heuristics
Simulation and Implementation
- Constructing multi-robot simulations within ROS 2 and Gazebo
- Implementing swarm behaviours using Python or C++
- Debugging and analysing emergent dynamics
Advanced Topics in Swarm Robotics
- Scalability, fault tolerance, and communication resilience
- Integrating machine learning for adaptive coordination
- Human-swarm interaction and supervisory control mechanisms
Practical Project: Designing and Simulating a Swarm Coordination System
- Defining objectives and constraints for a multi-robot mission
- Implementing swarm coordination algorithms
- Evaluating performance metrics and system robustness
Summary and Future Directions
Requirements
- A solid grasp of robotics fundamentals
- Proficiency in Python programming and ROS
- Knowledge of algorithms for motion planning and control
Target Audience
- Robotics researchers specialising in distributed and cooperative systems
- System architects developing large-scale multi-agent robotic solutions
- Senior developers engaged in autonomous coordination and swarm algorithms
28 Hours
Testimonials (2)
Supply of the materials (virtual machine) to get straight into the excersises, and the explanation of the Ros2 core. Why things work a certain way.
Arjan Bakema
Course - Autonomous Navigation & SLAM with ROS 2
its knowledge and utilization of AI for Robotics in the Future.
