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Course Outline
Introduction to Multi-Robot Systems
- Overview of multi-robot coordination and control architectures
- Applications across industry, research, and autonomous systems
- Comparing centralised versus decentralised systems
Fundamentals of Swarm Intelligence
- Principles of collective intelligence and self-organisation
- Biological inspirations: ants, bees, and flocks
- Emergent behaviour and robustness in swarm systems
Communication and Coordination
- Inter-robot communication models and protocols
- Consensus algorithms and distributed agreement
- Strategies for task allocation and resource sharing
Control and Formation Strategies
- Leader-follower, behaviour-based, and virtual structure control
- 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 in path planning and dynamic task assignment
- Hybrid approaches combining learning and swarm heuristics
Simulation and Implementation
- Constructing multi-robot simulations in 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
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 robustness
Summary and Next Steps
Requirements
- A solid grasp of robotics fundamentals
- Proficiency in Python programming and the ROS ecosystem
- Knowledge of algorithms related to motion planning and control
Target Audience
- Robotics researchers specialising in distributed and cooperative systems
- System architects designing large-scale multi-agent robotic solutions
- Senior developers working 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.