Research Article
Collective Decision Making in a Swarm of Robots: How Robust the BEECLUST Algorithm Performs in Various Conditions
@INPROCEEDINGS{10.4108/eai.3-12-2015.2262332, author={Daniela Kengyel and Payam Zahadat and Thomas Kunzfeld and Thomas Schmickl}, title={Collective Decision Making in a Swarm of Robots: How Robust the BEECLUST Algorithm Performs in Various Conditions}, proceedings={9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)}, publisher={ACM}, proceedings_a={BICT}, year={2016}, month={5}, keywords={swarm robotics autonomous agents self-organisation bio-inspired algorithm swarm intelligence collective decision making search}, doi={10.4108/eai.3-12-2015.2262332} }- Daniela Kengyel
Payam Zahadat
Thomas Kunzfeld
Thomas Schmickl
Year: 2016
Collective Decision Making in a Swarm of Robots: How Robust the BEECLUST Algorithm Performs in Various Conditions
BICT
EAI
DOI: 10.4108/eai.3-12-2015.2262332
Abstract
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.
