A control Lyapunov function approach to multi-agent coordination

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 01 Oct 2002 Sweden, United States Publisher:IEEEJournal:Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)

Authors: Petter Ögren; Magnus Egerstedt; Xiaoming Hu 0001;

doi: 10.1109/.2001.981040 , 10.1109/cdc.2001.981040 , 10.1109/tra.2002.804500

handle: 1853/38563

A control Lyapunov function approach to multi-agent coordination

- Summary
- Subjects
- Metrics

Abstract

In this paper, the multiagent coordination problem is studied. This problem is addressed for a class of robots for which control Lyapunov functions can be found. The main result is a suite of theorems about formation maintenance, task completion time, and formation velocity. It is also shown how to moderate the requirement that, for each individual robot, there exists a control Lyapunov function. An example is provided that illustrates the soundness of the method.

Countries

Sweden, United States

Related Organizations

Harvard University
United States
Royal Institute of Technology
Sweden
Georgia Institute of Technology
United States

Keywords

Robot formation control, 629, Coordinated control, Computer and Information Sciences, Mobile robots, Multi-robot systems, Data- och informationsvetenskap, Lyapunov methods

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	295
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 0.1%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 1%