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Duration 28 hours
Course Outline
Introduction to Multi-Robot Systems
- Overview of coordination and control architectures for multi-robot setups
- Industrial, research, and autonomous system applications
- Comparative analysis of centralized versus decentralized systems
Fundamentals of Swarm Intelligence
- Core principles of collective intelligence and self-organization
- Biological inspirations: ants, bees, and flocks
- Emergent behaviors and robustness 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, behavior-based, and virtual structure control methods
- Algorithms for flocking, coverage, and pursuit–evasion
- Maintaining formation under noisy communication conditions
Swarm Optimization Algorithms
- Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)
- Applications in path planning and dynamic task assignment
- Hybrid approaches integrating learning and swarm heuristics
Simulation and Implementation
- Developing multi-robot simulations in ROS 2 and Gazebo
- Implementing swarm behaviors using Python or C++
- Debugging and analyzing 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
Practical 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
Conclusion and Next Steps
Requirements
- A solid understanding of robotics fundamentals
- Proficiency in Python programming and ROS
- Familiarity with algorithms for motion planning and control
Target Audience
- Robotics researchers specializing in distributed and cooperative systems
- System architects creating large-scale multi-agent robotic solutions
- Advanced 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.
