Bearing-Distance Flocking with Zone-Based Interactions in Constrained Dynamic Environments

TL;DR

This paper introduces a zone-based flocking control method for multi-agent systems that relies solely on bearing and distance measurements, enabling scalable, robust, and adaptable flocking behavior in dynamic environments.

Contribution

The paper proposes a novel bearing-distance flocking control approach with zone-based behavioral rules, including obstacle avoidance, suitable for dynamic multi-agent systems with limited sensing.

Findings

Effective flocking behavior demonstrated in simulations

Ensures stability and convergence under certain graph conditions

Applicable to real-world dynamic and resource-constrained environments

Abstract

This paper presents a novel zone-based flocking control approach suitable for dynamic multi-agent systems (MAS). Inspired by Reynolds behavioral rules for $boids$, flocking behavioral rules with the zones of repulsion, conflict, attraction, and surveillance are introduced. For each agent, using only bearing and distance measurements, behavioral contribution vectors quantify the local separation, local and global flock velocity alignment, local cohesion, obstacle avoidance and boundary conditions, and strategic separation for avoiding alien agents. The control strategy uses the local perception-based behavioral contribution vectors to guide each agent's motion. Additionally, the control strategy incorporates a directionally aware obstacle avoidance mechanism that prioritizes obstacles in the agent's forward path. Simulation results validate the effectiveness of the model in creating flexible, adaptable, and scalable flocking behavior. Asymptotic stability and convergence to a stable flocking configuration for any initial conditions provided the interaction graph is a spanning tree are demonstrated. The flocking model's reliance on locally sensed bearing and distance measurements ensures scalability and robustness, particularly in scenarios where communication is unreliable or resource-intensive. This makes it well-suited for real-world applications demanding seamless operation in highly dynamic and distributed environments.