A distance weighted-based approach for self-organized aggregation in robot swarms
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Applied Mathematics and Computational Science Program
KAUST Grant NumberOSR-2015-CRG4-2582
MetadataShow full item record
AbstractIn 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.
CitationKhaldi B, Harrou F, Cherif F, Sun Y (2017) A distance weighted-based approach for self-organized aggregation in robot swarms. 2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B). Available: http://dx.doi.org/10.1109/ICEE-B.2017.8192133.
SponsorsThis 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.