Synchronization of multi-agent systems with metric-topological interactions

Area of Science:

• Robotics
• Complex Systems
• Control Theory

Background:

• Multi-agent systems (MAS) often rely on metric-only or topological-only interaction rules.
• These conventional models have limitations in achieving robust and efficient group coordination.
• Bridging the gap between metric and topological interactions is crucial for advanced MAS applications.

Purpose of the Study:

• To develop a novel hybrid metric-topological model for multi-agent systems.
• To analyze the conditions ensuring group synchronization in planar motion.
• To investigate the model's robustness and performance against variations in system parameters.

Main Methods:

• Development of a hybrid multi-agent systems model integrating metric and topological interaction rules.
• Analysis of sufficient conditions for group synchronization based on system parameters and initial states.
• Comparative study of the hybrid model against metric-only and topological-only models.

Main Results:

• The metric-topological model enables agents to interact within a constant radius and with a specific number of neighbors.
• Sufficient conditions for achieving group synchronization were identified.
• The hybrid model consistently outperformed metric-only and topological-only models in synchronization frequency, convergence rate, and heading difference.

Conclusions:

• The hybrid metric-topological model offers enhanced performance for mobile agent synchronization.
• The model reveals intrinsic relationships between interaction range, speed, initial heading, and group density.
• This approach provides a more robust and efficient framework for coordinated multi-agent behaviors.