Coordination of a Semi-Informed Flocking System via Model Predictive Control

Abstract

Coordination of mobile multi-agent systems has been studied intensively for many different purposes. These include swarm robotics, transportation, control of human crowds, and even understanding of collective behavior of animal groups. Mainly, the flocking behavior of multiple agents has been investigated under usually idealized conditions regarding information availability. This paper proposes a model predictive control framework to control flocking agents with limited information. The flocking system is composed of a leader agent and agents that have no information about the group objective and cannot perceive the unknown operation area. The leader agent is a part of the group. However, it has prior information about the group objective and can sense the environment. With the proposed control scheme, the leader steers the flocking agents like a shepherd dog to accomplish the group goal. The presented control scheme is validated in simulation examples.