Flocking fragmentation formulation for a multi-robot system under multi-hop and lossy ad hoc networks

作     者：Silan LI Shengyu ZHANG Tao JIANG Silan LI;Shengyu ZHANG;Tao JIANG

作者机构：The Research Center of 6G Mobile CommunicationsSchool of Cyber Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan 430074China 

出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)

年 卷 期：2024年第25卷第8期

页      面：1057-1076页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Key Research and Development Program of China(No.2019YFB1803400) 

主　　题：Multi-robot flocking Flocking fragmentation probability Fragmentation prediction Multi-robot communication networks 

摘      要：We investigate the impact of network topology characteristics on focking fragmentation for a multi-robot system under a multi-hop and lossy ad hoc network,including the network s hop count features and information s successful transmission probability(STP).Specifically,we first propose a distributed communication calculation execution protocol to describe the practical interaction and control process in the ad hoc network based multi-robot system,where focking control is realized by a discrete-time Olfati-Saber model incorporating STP-related ***,we develop a fragmentation prediction model(FPM)to formulate the impact of hop count features on fragmentation for specific focking *** model identifies the critical system and network features that are associated with *** considering general focking scenarios affected by both hop count features and STP,we formulate the flocking fragmentation probability(FFP)by a data fitting model based on the back propagation neural network,whose input is extracted from the *** FFP formulation quantifies the impact of key network topology characteristics on fragmentation *** results verify the effectiveness and accuracy of the proposed prediction model and FFP formulation,and several guidelines for constructing the multi-robot ad hoc network are concluded.