Research Article
Self-organised Flocking with Simulated Homogeneous Robotic Swarm
@INPROCEEDINGS{10.1007/978-3-030-67540-0_1, author={Zhe Ban and Craig West and Barry Lennox and Farshad Arvin}, title={Self-organised Flocking with Simulated Homogeneous Robotic Swarm}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 16th EAI International Conference, CollaborateCom 2020, Shanghai, China, October 16--18, 2020, Proceedings, Part II}, proceedings_a={COLLABORATECOM PART 2}, year={2021}, month={1}, keywords={Swarm robotics Flocking Self-organised Collective behaviour}, doi={10.1007/978-3-030-67540-0_1} }- Zhe Ban
Craig West
Barry Lennox
Farshad Arvin
Year: 2021
Self-organised Flocking with Simulated Homogeneous Robotic Swarm
COLLABORATECOM PART 2
Springer
DOI: 10.1007/978-3-030-67540-0_1
Abstract
Flocking is a common behaviour observed in social animals such as birds and insects, which has received considerable attention in swarm robotics research studies. In this paper, a homogeneous self-organised flocking mechanism was implemented using simulated robots to verify a collective model. We identified and proposed solutions to the current gap between the theoretical model and the implementation with real-world robots. Quantitative experiments were designed with different factors which are swarm population size, desired distance between robots and the common goal force. To evaluate the group performance of the swarm, the average distance within the flock was chosen to show the coherency of the swarm, followed by statistical analysis to investigate the correlation between these factors. The results of the statistical analysis showed that compared with other factors, population size had a significant impact on the swarm flocking performance. This provides guidance on the application with real robots in terms of factors and strategic design.
