How Much Control is Enough for Network Connectivity Preservation and Collision Avoidance?

Area of Science:

• Robotics
• Control Theory
• Multiagent Systems

Background:

• Multiagent systems require balancing cohesive and repulsive forces for network connectivity and collision avoidance.
• Existing methods may not offer a generalizable approach for estimating these control forces.

Purpose of the Study:

• To develop an energy function-based approach for estimating control forces in multiagent systems.
• To separate forces for network connectivity preservation and collision avoidance from other collective behaviors.
• To apply the estimation approach to swarming, flocking, and flocking without velocity measurement.

Main Methods:

• An energy function is utilized to estimate the required control forces.
• The approach separates the estimation of cohesive and repulsive forces.
• The method is demonstrated in three distinct collective control scenarios.

Main Results:

• The proposed energy function approach effectively estimates control forces for network connectivity and collision avoidance.
• The separation of forces allows for more targeted control of collective behaviors.
• Successful application demonstrated in swarming, flocking, and velocity-less flocking.

Conclusions:

• The energy function-based method provides a generalizable framework for multiagent control.
• This approach enhances network connectivity and ensures collision avoidance in dynamic environments.
• The findings are applicable to various collective behaviors in multiagent systems.