Course Outline
Introduction to Multi-Robot Systems
- Overview of coordination and control architectures for multi-robot environments.
- Key applications across industry, research, and autonomous system sectors.
- Analytical comparison between centralized and decentralized system structures.
Fundamentals of Swarm Intelligence
- Core principles of collective intelligence and self-organization.
- Biological inspirations drawn from ants, bees, and bird flocks.
- The role of emergent behavior in enhancing the robustness of swarm systems.
Communication and Coordination
- Models and protocols for inter-robot communication.
- Consensus algorithms and mechanisms for distributed agreement.
- Strategies for efficient task allocation and resource sharing.
Control and Formation Strategies
- Examination of leader-follower, behavior-based, and virtual structure control methods.
- Algorithms for flocking, coverage, and pursuit–evasion scenarios.
- Maintaining formation integrity under conditions of noisy or unreliable communication.
Swarm Optimization Algorithms
- Detailed study of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO).
- Application of these techniques to path planning and dynamic task assignment.
- Hybrid approaches that integrate learning techniques with swarm heuristics.
Simulation and Implementation
- Construction of multi-robot simulation environments using ROS 2 and Gazebo.
- Implementation of swarm behaviors utilizing Python or C++.
- Techniques for debugging and analyzing emergent system dynamics.
Advanced Topics in Swarm Robotics
- Challenges and solutions regarding scalability, fault tolerance, and communication resilience.
- Integration of machine learning for adaptive coordination capabilities.
- Aspects of human-swarm interaction and supervisory control frameworks.
Hands-on Project: Design and Simulation of a Swarm Coordination System
- Definition of mission objectives and operational constraints for multi-robot tasks.
- Practical implementation of swarm coordination algorithms.
- Evaluation of system performance metrics and overall robustness.
Summary and Next Steps
Requirements
- A robust understanding of fundamental robotics concepts.
- Proficiency in Python programming and experience with ROS.
- Familiarity with algorithms related to motion planning and control systems.
Target Audience
- Robotics researchers specializing in distributed and cooperative system architectures.
- System architects involved in designing large-scale, multi-agent robotic solutions.
- Senior developers focused on autonomous coordination mechanisms and swarm algorithms.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 5200 € + VAT*
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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.
