VMCS: Elaborating APF-Based Swarm Intelligence for Mission-Oriented Multi-UV Control

Abstract

This paper addresses a novel approach for multi-agent control systems including Unmanned Vehicles (UV). As UV technology advances, one or a group of UVs can be used in a wide range of industrial or military applications. Centralized monitoring has limitations on various resources (e.g. communication bandwidth, propagation delay, and computational power), but can lead to an optimal solution to the movement of the swarm. The artificial potential field (APF) method is well-known for modeling decentralized behavior, but most APF research only focuses on naive actions such as collision avoidance, flocking, or path planning. In our proposed design Versatile Multi-Vehicle Control System (VMCS), we defined high-level conditions as APF and let UVs perform swarm intelligence in various mission environments. Furthermore, we devised a novel algorithm that controls the UVs' APF topology which can significantly enhance the mission efficiency. We simulated the VMCS in 3D space and showed our scheme can control the dynamic mission scenarios for multi-UV systems.