基于voronoi的无人机编队部署与MPC重新配置

T. Chevet, C. Maniu, C. Vlad, Youmin Zhang
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引用次数: 14

摘要

本文提出了一种基于分散voronoi的线性模型预测控制(MPC)技术,用于在限定区域内由无人机组成的多智能体系统的部署和重构。在每个时刻,该区域被划分为与每个无人机代理相关联的不重叠的时变Voronoi单元。编队部署的目标是基于每个Voronoi单元的Chebyshev中心将代理驱动到静态配置中。提出的基于mpc的地层重构算法不仅允许故障/不合作的agent离开地层,还允许恢复/健康的agent加入当前的地层,同时避免碰撞。仿真结果验证了所提控制算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Voronoi-based UAVs Formation Deployment and Reconfiguration using MPC Techniques
This paper presents a decentralized Voronoi-based linear model predictive control (MPC) technique for the deployment and reconfiguration of a multi-agent system composed of unmanned aerial vehicles (UAVs) in a bounded area. At each time instant, this area is partitioned into non-overlapping time-varying Voronoi cells associated to each UAV agent. The formation deployment objective is to drive the agents into a static configuration based on the Chebyshev center of each Voronoi cell. The proposed MPC-based formation reconfiguration algorithms allow not only faulty/non-cooperating agents to leave the formation, but also recovered/healthy agents to join in the current formation, while avoiding collisions. Simulation results validate the effectiveness of the proposed control algorithms.
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