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Course Outline
Introduction to Multi-Robot Systems
- Survey of multi-robot coordination and control architectures
- Industrial, research, and autonomous system applications
- Evaluation of centralized versus decentralized system models
Core Concepts of Swarm Intelligence
- Fundamentals of collective intelligence and self-organization
- Bio-inspired mechanisms from ants, bees, and bird flocks
- Emergent properties and system robustness in swarm contexts
Communication and Coordination Protocols
- Models and protocols for inter-robot communication
- Consensus algorithms and mechanisms for distributed agreement
- Strategies for task allocation and resource distribution
Control and Formation Tactics
- Techniques including leader-follower, behavior-based, and virtual structure control
- Algorithms for flocking, coverage, and pursuit–evasion
- Maintaining formation integrity amidst noisy communication environments
Swarm Optimization Techniques
- Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) methods
- Application to path planning and dynamic task assignment
- Hybrid models integrating learning with swarm heuristics
Simulation and Practical Implementation
- Constructing multi-robot simulations using ROS 2 and Gazebo
- Coding swarm behaviors in Python or C++
- Debugging and assessing emergent system dynamics
Advanced Aspects of Swarm Robotics
- Addressing scalability, fault tolerance, and communication resilience
- Integrating machine learning for adaptive coordination
- Human-swarm interaction models and supervisory control
Practical Project: Designing and Simulating a Swarm Coordination System
- Establishing objectives and constraints for multi-robot missions
- Coding and deploying swarm coordination algorithms
- Assessing performance metrics and system robustness
Conclusion and Future Directions
Requirements
- Solid grasp of fundamental robotics concepts
- Proficiency in Python programming and the ROS ecosystem
- Knowledge of algorithms related to motion planning and control
Target Audience
- Robotics researchers specializing in distributed and cooperative systems
- System architects engineering 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.