Morphogen diffusion algorithms for tracking and herding using a swarm of kilobots
journal contributionposted on 2016-06-09, 10:20 authored by Hd Oh, Ataollah R. Shiraz, Yaochu Jin
© 2016 Springer-Verlag Berlin Heidelberg This paper investigates self-organised collective formation control using swarm robots. In particular, we focus on collective tracking and herding using a large number of very simple robots. To this end, we choose kilobots as our swarm robot test bed due to its low cost and attractive operational scalability. Note, however, that kilobots have extremely limited locomotion, sensing and communication capabilities. To handle these limitations, a number of new control algorithms based on morphogen diffusion and network connectivity preservation have been suggested for collective object tracking and herding. Numerical simulations of large-scale swarm systems as well as preliminary physical experiments with a relatively small number of kilobots have been performed to verify the effectiveness of the proposed algorithms.
This work was funded by the European Commission 7th Framework Program, Project No. 601062, SWARM-ORGAN.
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering
Published inSoft Computing
Pages1 - 12
CitationOH, H., SHIRAZ, A.R. and JIN, Y., 2016. Morphogen diffusion algorithms for tracking and herding using a swarm of kilobots. Soft Computing, 22 (6), pp.1833–1844.
- AM (Accepted Manuscript)
Publisher statementThis work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
NotesThe final publication is available at Springer via http://dx.doi.org/10.1007/s00500-016-2182-2.