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Duration 28 hours (4 days)
Course Outline
Introduction to Multi-Robot Systems
- Overview of coordination and control architectures for multi-robot setups
- Applications across industry, research, and autonomous systems
- Analysis of centralized versus decentralized system architectures
Foundations of Swarm Intelligence
- Key principles of collective intelligence and self-organization
- Bio-inspired models: ants, bees, and bird flocks
- Emergent behaviors and system robustness in swarms
Communication and Coordination Mechanisms
- Models and protocols for inter-robot communication
- Consensus algorithms and strategies for distributed agreement
- Approaches to task allocation and resource sharing
Control and Formation Techniques
- Leader-follower models, behavior-based control, and virtual structures
- Algorithms for flocking, coverage, and pursuit–evasion
- Maintaining formations under conditions of noisy communication
Swarm Optimization Algorithms
- Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)
- Use cases in path planning and dynamic task assignment
- Hybrid methods integrating learning techniques with swarm heuristics
Simulation and Implementation
- Developing multi-robot simulations using ROS 2 and Gazebo
- Implementing swarm behaviors in Python or C++
- Debugging and analyzing emergent system dynamics
Advanced Topics in Swarm Robotics
- Scalability, fault tolerance, and communication resilience
- Integrating machine learning for adaptive coordination
- Human-swarm interaction and supervisory control frameworks
Practical Project: Designing and Simulating a Swarm Coordination System
- Setting objectives and constraints for a multi-robot mission
- Implementing swarm coordination algorithms
- Assessing performance metrics and system robustness
Summary and Future Directions
Requirements
- Solid grasp of robotics fundamentals
- Proficiency in Python programming and ROS
- Knowledge of algorithms for motion planning and control
Target Audience
- Robotics researchers specializing in distributed and cooperative systems
- System architects developing large-scale multi-agent robotic solutions
- Senior developers working on autonomous coordination and swarm algorithms
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.