分布式多智能体网络定位的线性理论与算法综述  

Survey of distributed multi-agent network localization:Linear theory and algorithms

作　　者：林志赟 吴金泽 陈亮名 LIN Zhi-yun;WU Jin-ze;CHEN Liang-ming(School of System Design and Intelligent Manufacturing,Southern University of Science and Technology,Shenzhen 518055,China;Shenzhen Key Laboratory of Control Theory and Intelligent Systems,Southern University of Science and Technology,Shenzhen 518055,China;PengCheng Laboratory,Shenzhen 518000,China)

机构地区：[1]南方科技大学系统设计与智能制造学院,广东深圳518055 [2]南方科技大学深圳市控制理论与智能系统重点实验室,广东深圳518055 [3]鹏城实验室,广东深圳518000

出　　处：《控制与决策》2024年第2期353-370,共18页Control and Decision

基　　金：国家自然科学基金项目(62173118);深圳市科技计划项目(KQTD20221101093557010);深圳市控制理论与智能系统重点实验室项目(ZDSYS20220330161800001)。

摘　　要：多智能体网络定位在智慧物流、工厂监控、无人系统集群等领域具有广阔的应用,然而网络中节点测量量相对于节点位置的非线性本质给定位问题带来了巨大的挑战.鉴于此,对分布式多智能体网络定位问题进行综述.首先通过比较分析非线性定位方法与线性定位方法以及集中式定位方法与分布式定位方法,凸显了分布式线性定位方法的明显优势;然后从可定位性的判定条件与线性定位算法两个方面对目前已有的相关成果进行梳理与综述,其中包括距离、方位角、相对位置以及内角等4种测量量下的相关结果;最后总结目前尚未解决的难题以及未来的研究方向.Multi-agent network localization has broad applications in many fields,such as intelligent logistics,factory monitoring,and swarms of unmanned systems.However,the nonlinearity of sensor node measurements with respect to node positions poses great challenges for localization.This paper surveys existing results on multi-agent network localization.Firstly,we compare linear and nonlinear localization approaches,as well as centralized and distributed approaches,from which we can see many advantages of distributed linear localization.Then,we review recent progress on localizability conditions and distributed localization algorithms for multi-agent networks with common measurements such as distances,bearings,local relative positions,and interior angles.Multi-agent network localization remains an active area with many open problems that are discussed finally.

关 键 词：多智能体系统 网络定位 分布式算法 线性定位理论 局部测量 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]