A Software Framework for Self-Organized Flocking System Motion Coordination Research

Abstract

We describe and analyze the basic algorithms for the self-organization of a swarm of robots in coordinated motion as a flock of agents as a strategy for the solution of multi-agent tasks. This analysis allows us to postulate a simulation framework for such systems based on the behavioral rules that characterize the dynamics of these systems. The problem is approached from the perspective of autonomous navigation in an unknown but restricted and locally observable environment. The simulation framework allows defining individually the characteristics of the basic behaviors identified as fundamental to show a flocking behavior, as well as the specific characteristics of the navigation environment. It also allows the incorporation of different path planning approaches to enable the system to navigate the environment for different strategies, both geometric and reactive. The basic behaviors modeled include safe wandering, following, aggregation, dispersion, and homing, which interact to generate flocking behavior, i.e., the swarm aggregates, reach a stable formation and move in an organized fashion toward the target point. The framework concept follows the principle of constrained target tracking, which allows the problem to be solved similarly as a small robot with limited computation would solve it. It is shown that the algorithm and the framework that implements it are robust to the defined constraints and manage to generate the flocking behavior while accomplishing the navigation task. These results provide key guidelines for the implementation of these algorithms on real platforms.