A Flocking Behavior Model with Artificial Potential Fields for the Coordinated Displacement of Robotic Swarms

This paper presents a reactive behavior model for mobile robotic swarms, developed by integrating a biologically inspired method of swarm intelligence known as flocking and an algorithm of artificial potential fields. The resulting reactive behavior model, firstly, prevents collisions between the different agents and constitutes the swarm as a group (flocking model), and secondly, achieves the displacement of the robotic swarm while avoiding the obstacles of the environment (artificial potential fields). This is accomplished without the requirement of a leader or central agent, nor the predefinition of a positioning pattern for the agents. The problem is solved using a simplified swarm behavior model equally programmed in each agent. The proposed model is synthesized such that each agent may calculate its own linear and angular velocities, allowing the implementation of the behavior by introducing those velocities into the kinematic model of each robotic agent.