Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 155 tok/s
Gemini 2.5 Pro 43 tok/s Pro
GPT-5 Medium 20 tok/s Pro
GPT-5 High 20 tok/s Pro
GPT-4o 86 tok/s Pro
Kimi K2 184 tok/s Pro
GPT OSS 120B 446 tok/s Pro
Claude Sonnet 4.5 31 tok/s Pro
2000 character limit reached

Decentralized Formation Control Part II: Algebraic aspects of information flow and singularities (1101.2421v2)

Published 12 Jan 2011 in math.OC, cs.MA, and cs.SY

Abstract: Given an ensemble of autonomous agents and a task to achieve cooperatively, how much do the agents need to know about the state of the ensemble and about the task in order to achieve it? We introduce new methods to understand these aspects of decentralized control. Precisely, we introduce a framework to capture what agents with partial information can achieve by cooperating and illustrate its use by deriving results about global stabilization of directed formations. This framework underscores the need to differentiate the knowledge an agent has about the task to accomplish from the knowledge an agent has about the current state of the system. The control of directed formations has proven to be more difficult than initially thought, as is exemplified by the lack of global result for formations with n \geq 4 agents. We established in part I that the space of planar formations has a non-trivial global topology. We propose here an extension of the notion of global stability which, because it acknowledges this non-trivial topology, can be applied to the study of formation control. We then develop a framework that reduces the question of whether feedback with partial information can stabilize the system to whether two sets of functions intersect. We apply this framework to the study of a directed formation with n = 4 agents and show that the agents do not have enough information to implement locally stabilizing feedback laws. Additionally, we show that feedback laws that respect the information flow cannot stabilize a target configuration without stabilizing other, unwanted configurations.

Citations (4)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Authors (1)

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.