Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Multi-Robot Systems
- Review of multi-robot coordination and control architectures
- Industrial, research, and autonomous system applications
- Distinguishing centralized versus decentralized systems
Fundamentals of Swarm Intelligence
- Core principles of collective intelligence and self-organization
- Biological analogs: ants, bees, and bird flocks
- Emergent behavior and system robustness in swarms
Communication and Coordination
- Models and protocols for inter-robot communication
- 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 formations under noisy communication conditions
Swarm Optimization Algorithms
- Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)
- Application to path planning and dynamic task assignment
- Hybrid approaches integrating learning with swarm heuristics
Simulation and Implementation
- Constructing multi-robot simulations using ROS 2 and Gazebo
- Implementing swarm behaviors via 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
Hands-on Project: Design and Simulation of a Swarm Coordination System
- Defining mission objectives and constraints for a multi-robot setup
- Implementing swarm coordination algorithms
- Evaluating performance metrics and system robustness
Summary and Next Steps
Requirements
- Solid foundation in robotics fundamentals
- 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 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.