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Course Outline
Introduction to Multi-Robot Systems
- Overview of coordination and control architectures in multi-robot environments
- Applications across industry, research, and autonomous systems
- Comparison between centralised and decentralised system approaches
Fundamentals of Swarm Intelligence
- Principles of collective intelligence and self-organisation
- Biological inspiration drawn from ants, bees, and flocks
- Emergent behaviour and robustness characteristics in swarm systems
Communication and Coordination
- Inter-robot communication models and protocols
- Consensus algorithms and distributed agreement mechanisms
- Strategies for task allocation and resource sharing
Control and Formation Strategies
- Leader-follower, behaviour-based, and virtual structure control methods
- Flocking, coverage, and pursuit–evasion algorithms
- Maintaining formation under noisy communication conditions
Swarm Optimisation Algorithms
- Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO)
- Applications to path planning and dynamic task assignment
- Hybrid approaches integrating 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
- Integration of machine learning for adaptive coordination
- Human-swarm interaction and supervisory control
Hands-on Project: Design and Simulation of 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 Next Steps
Requirements
- A solid grasp of robotics fundamentals
- Practical experience with Python programming and ROS
- Knowledge of algorithms related to motion planning and control
Audience
- Robotics researchers specialising in distributed and cooperative systems
- System architects developing large-scale multi-agent robotic solutions
- Senior developers focused on 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.