Asynchronous Network Formation in Unknown Unbounded Environments

Loading...
Thumbnail Image

View/Download File

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Asynchronous Network Formation in Unknown Unbounded Environments

Published Date

2018-09-17

Publisher

Type

Report

Abstract

In this paper, we study the Online Network Formation Problem (ONFP) for a mobile multi-robot system. Consider a group of robots with a bounded communication range operating in a large open area. One of the robots has a piece of information which has to be propagated to all other robots. What strategy should the robots pursue to disseminate the information to the rest of the robots as quickly as possible? The initial locations of the robots are unknown to each other, therefore the problem must be solved in an online fashion. For this problem, we present an algorithm whose competitive ratio is $O(H cdot max{M,sqrt{M H}})$ for arbitrary robot deployments, where $M$ is the largest edge length in the Euclidean minimum spanning tree on the initial robot configuration and $H$ is the height of the tree. We also study the case when the robot initial positions are chosen uniformly at random and improve the ratio to $O(M)$. Finally, we present simulation results to validate the performance in larger scales and demonstrate our algorithm using three robots in a field experiment.

Keywords

Description

Related to

Replaces

License

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Suggested citation

Engin, Selim; Isler, Volkan. (2018). Asynchronous Network Formation in Unknown Unbounded Environments. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/216032.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.