A Distributed Optimization Framework for Localization and Formation Control

Applications to Vision-Based Measurements

Roberto Tron, Justin Thomas, Giuseppe Loianno, Kostas Daniilidis, Vijay Kumar

Research output: Contribution to journalArticle

Abstract

Multiagent systems have been a major area of research for the last 15 years. This interest has been motivated by tasks that can be executed more rapidly in a collaborative manner or that are nearly impossible to carry out otherwise. To be effective, the agents need to have the notion of a common goal shared by the entire network (for instance, a desired formation) and individual control laws to realize the goal. The common goal is typically centralized, in the sense that it involves the state of all the agents at the same time. On the other hand, it is often desirable to have individual control laws that are distributed, in the sense that the desired action of an agent depends only on the measurements and states available at the node and at a small number of neighbors. This is an attractive quality because it implies an overall system that is modular and intrinsically more robust to communication delays and node failures.

Original languageEnglish (US)
Article number7515271
Pages (from-to)22-44
Number of pages23
JournalIEEE Control Systems
Volume36
Issue number4
DOIs
StatePublished - Jul 1 2016

Fingerprint

Distributed Optimization
Formation Control
Communication Delay
Vertex of a graph
Multi agent systems
Multi-agent Systems
Entire
Imply
Communication
Vision
Framework

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Electrical and Electronic Engineering

Cite this

A Distributed Optimization Framework for Localization and Formation Control : Applications to Vision-Based Measurements. / Tron, Roberto; Thomas, Justin; Loianno, Giuseppe; Daniilidis, Kostas; Kumar, Vijay.

In: IEEE Control Systems, Vol. 36, No. 4, 7515271, 01.07.2016, p. 22-44.

Research output: Contribution to journalArticle

Tron, Roberto ; Thomas, Justin ; Loianno, Giuseppe ; Daniilidis, Kostas ; Kumar, Vijay. / A Distributed Optimization Framework for Localization and Formation Control : Applications to Vision-Based Measurements. In: IEEE Control Systems. 2016 ; Vol. 36, No. 4. pp. 22-44.
@article{fde2f489c10a401bac45141782cc770f,
title = "A Distributed Optimization Framework for Localization and Formation Control: Applications to Vision-Based Measurements",
abstract = "Multiagent systems have been a major area of research for the last 15 years. This interest has been motivated by tasks that can be executed more rapidly in a collaborative manner or that are nearly impossible to carry out otherwise. To be effective, the agents need to have the notion of a common goal shared by the entire network (for instance, a desired formation) and individual control laws to realize the goal. The common goal is typically centralized, in the sense that it involves the state of all the agents at the same time. On the other hand, it is often desirable to have individual control laws that are distributed, in the sense that the desired action of an agent depends only on the measurements and states available at the node and at a small number of neighbors. This is an attractive quality because it implies an overall system that is modular and intrinsically more robust to communication delays and node failures.",
author = "Roberto Tron and Justin Thomas and Giuseppe Loianno and Kostas Daniilidis and Vijay Kumar",
year = "2016",
month = "7",
day = "1",
doi = "10.1109/MCS.2016.2558401",
language = "English (US)",
volume = "36",
pages = "22--44",
journal = "IEEE Control Systems",
issn = "1066-033X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "4",

}

TY - JOUR

T1 - A Distributed Optimization Framework for Localization and Formation Control

T2 - Applications to Vision-Based Measurements

AU - Tron, Roberto

AU - Thomas, Justin

AU - Loianno, Giuseppe

AU - Daniilidis, Kostas

AU - Kumar, Vijay

PY - 2016/7/1

Y1 - 2016/7/1

N2 - Multiagent systems have been a major area of research for the last 15 years. This interest has been motivated by tasks that can be executed more rapidly in a collaborative manner or that are nearly impossible to carry out otherwise. To be effective, the agents need to have the notion of a common goal shared by the entire network (for instance, a desired formation) and individual control laws to realize the goal. The common goal is typically centralized, in the sense that it involves the state of all the agents at the same time. On the other hand, it is often desirable to have individual control laws that are distributed, in the sense that the desired action of an agent depends only on the measurements and states available at the node and at a small number of neighbors. This is an attractive quality because it implies an overall system that is modular and intrinsically more robust to communication delays and node failures.

AB - Multiagent systems have been a major area of research for the last 15 years. This interest has been motivated by tasks that can be executed more rapidly in a collaborative manner or that are nearly impossible to carry out otherwise. To be effective, the agents need to have the notion of a common goal shared by the entire network (for instance, a desired formation) and individual control laws to realize the goal. The common goal is typically centralized, in the sense that it involves the state of all the agents at the same time. On the other hand, it is often desirable to have individual control laws that are distributed, in the sense that the desired action of an agent depends only on the measurements and states available at the node and at a small number of neighbors. This is an attractive quality because it implies an overall system that is modular and intrinsically more robust to communication delays and node failures.

UR - http://www.scopus.com/inward/record.url?scp=84982216613&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84982216613&partnerID=8YFLogxK

U2 - 10.1109/MCS.2016.2558401

DO - 10.1109/MCS.2016.2558401

M3 - Article

VL - 36

SP - 22

EP - 44

JO - IEEE Control Systems

JF - IEEE Control Systems

SN - 1066-033X

IS - 4

M1 - 7515271

ER -