Emergence of Consensus in a Multi-Robot Network: from Abstract Models to Empirical Validation
Trianni, V., Simone, D. D., Reina, A. & Baronchelli, A. (2016). Emergence of Consensus in a Multi-Robot Network: from Abstract Models to Empirical Validation. Robotics and Automation Letters, IEEE, 1(1), pp. 348-353. doi: 10.1109/lra.2016.2519537
Abstract
Consensus dynamics in decentralised multiagent systems are subject to intense studies, and several different models have been proposed and analysed. Among these, the naming game stands out for its simplicity and applicability to a wide range of phenomena and applications, from semiotics to engineering. Despite the wide range of studies available, the implementation of theoretical models in real distributed systems is not always straightforward, as the physical platform imposes several constraints that may have a bearing on the consensus dynamics. In this paper, we investigate the effects of an implementation of the naming game for the kilobot robotic platform, in which we consider concurrent execution of games and physical interferences. Consensus dynamics are analysed in the light of the continuously evolving communication network created by the robots, highlighting how the different regimes crucially depend on the robot density and on their ability to spread widely in the experimental arena. We find that physical interferences reduce the benefits resulting from robot mobility in terms of consensus time, but also result in lower cognitive load for individual agents.
Publication Type: | Article |
---|---|
Additional Information: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Subjects: | Q Science > QA Mathematics |
Departments: | School of Science & Technology > Mathematics |
SWORD Depositor: |
Download (5MB) | Preview
Export
Downloads
Downloads per month over past year