Collective Decision Making in a Swarm of Robots: How Robust the BEECLUST Algorithm Performs in Various Conditions

In this paper a honeybee inspired collective-decision-making algorithm called BEECLUST is studied in a swarm of autonomous robots and the performance of the swarm is investigated in different conditions. The algorithm has low requirements thus it is promising for implementation in robots with low re...

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Bibliographic Details
Main Authors: Daniela Kengyel, Payam Zahadat, Thomas Kunzfeld, Thomas Schmickl
Format: Article
Language:English
Published: European Alliance for Innovation (EAI) 2016-12-01
Series:EAI Endorsed Transactions on Serious Games
Subjects:
Online Access:http://eudl.eu/doi/10.4108/eai.3-12-2015.2262332
Description
Summary:In this paper a honeybee inspired collective-decision-making algorithm called BEECLUST is studied in a swarm of autonomous robots and the performance of the swarm is investigated in different conditions. The algorithm has low requirements thus it is promising for implementation in robots with low resources. Here the algorithm is applied in swarms of improved e-puck robots in three different conditions in order to study the strengths and limitations of the algorithm. The collective system demonstrated a high performance in adapting to a dynamic environment as well as a very low sensitivity to additional robots with malfunctioning sensors. On the other hand the system shows an strong response to robots that act as social seeds influencing the decision-making of the swarm.
ISSN:2034-8800