A distance weighted-based approach for self-organized aggregation in robot swarms

Belkacem Khaldi, Fouzi Harrou, Foudil Cherif, Ying Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


In this paper, a Distance-Weighted K Nearest Neighboring (DW-KNN) topology is proposed to study self-organized aggregation as an emergent swarming behavior within robot swarms. A virtual physics approach is applied among the proposed neighborhood topology to keep the robots together. A distance-weighted function based on a Smoothed Particle Hydrodynamic (SPH) interpolation approach is used as a key factor to identify the K-Nearest neighbors taken into account when aggregating the robots. The intra virtual physical connectivity among these neighbors is achieved using a virtual viscoelastic-based proximity model. With the ARGoS based-simulator, we model and evaluate the proposed approach showing various self-organized aggregations performed by a swarm of N foot-bot robots.
Original languageEnglish (US)
Title of host publication2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Print)9781538606865
StatePublished - Dec 14 2017

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OSR-2015-CRG4-2582
Acknowledgements: This work is based upon a collaboration work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No: OSR-2015-CRG4-2582, and the LESIA Laboratory, Department of Computer Science, University of Mohamed Khider, Biskra, Algeria.


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