Distributed Control and Estimation of Robotic Vehicle Networks AN OVERVIEW OF PART 2

被引：4

作者：

Ahmed, Nisar R. ^{[1
]}

Cortes, Jorge ^{[2
,3
,4
,5
]}

Martinez, Sonia ^{[6
,7
,8
,9
]}

机构：

[1] Univ Colorado, Aerosp Engn Sci, Ctr Engn, 1111 Engn Dr,Room ECAE 197, Boulder, CO 80309 USA

[2] Univ Twente, POB 217, NL-7500 AE Enschede, Netherlands

[3] Univ Illinois, Urbana, IL 61801 USA

[4] Univ Calif Santa Cruz, Dept Appl Math & Stat, Santa Cruz, CA 95064 USA

[5] Univ Calif San Diego, Dept Mech & Aerosp Engn, San Diego, CA USA

[6] Univ Calif San Diego, Dept Mech & Aerosp Engn, San Diego, CA 92103 USA

[7] Tech Univ Catalonia, Appl Math, Barcelona, Spain

[8] Univ Illinois, Coordinated Sci Lab, 1101 W Springfield Ave, Urbana, IL 61801 USA

[9] UC Santa Barbara, Ctr Control Dynam Syst & Computat, Santa Barbara, CA USA

来源：

IEEE CONTROL SYSTEMS MAGAZINE | 2016年 / 36卷 / 04期

关键词：

D O I：

10.1109/MCS.2016.2558398

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The topic of distributed control and estimation (DCE) is of increasing relevance to robotic vehicle systems that share a fundamental need to accomplish multiple tasks across space and time that are beyond the capabilities of a single platform. The growing demand for autonomous mobile multirobot networks has stimulated broad interest in DCE strategies that naturally support cooperative, collaborative, and coordinated vehicle autonomy. When designed and implemented properly, the performance of distributed approaches can approach that of centralized methods, but they also provide better scalability, naturally parallelized computation, and resilience to communication loss and hardware failures. © 1991-2012 IEEE.

引用

页码：18 / 21

页数：4