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

3 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


Dive into the research topics of 'A distance weighted-based approach for self-organized aggregation in robot swarms'. Together they form a unique fingerprint.

Cite this