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 language | English (US) |
---|---|
Article number | 7515271 |
Pages (from-to) | 22-44 |
Number of pages | 23 |
Journal | IEEE Control Systems |
Volume | 36 |
Issue number | 4 |
DOIs | |
State | Published - Jul 1 2016 |
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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 journal › Article
}
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.
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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
AN - SCOPUS:84982216613
VL - 36
SP - 22
EP - 44
JO - IEEE Control Systems
JF - IEEE Control Systems
SN - 1066-033X
IS - 4
M1 - 7515271
ER -