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Course Outline
Introduction to Multi-Robot Systems
- Overview of coordination and control architectures in multi-robot settings
- Industry, research, and autonomous system applications
- Contrasting centralized versus decentralized system architectures
Core Concepts of Swarm Intelligence
- Principles of collective intelligence and self-organization
- Biological inspirations derived from 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 achieving distributed agreement
- Strategies for task allocation and resource sharing
Control and Formation Techniques
- Leader-follower, behavior-based, and virtual structure control methods
- 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)
- Utilizing these techniques for path planning and dynamic task assignment
- Hybrid approaches that blend learning with swarm heuristics
Simulation and Practical Implementation
- Developing multi-robot simulations within ROS 2 and Gazebo
- Building swarm behaviors using Python or C++
- Debugging and analyzing emergent system dynamics
Advanced Topics in Swarm Robotics
- Addressing 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
- Defining mission objectives and constraints for multi-robot tasks
- Implementing coordination algorithms for swarm behavior
- Assessing performance metrics and system robustness
Wrap-Up and Future Directions
Requirements
- A solid grasp of fundamental robotics concepts
- Proficiency in Python programming and ROS
- Knowledge of algorithms related to 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 engaged in autonomous coordination and swarm algorithm development
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.