Improving robots swarm aggregation performance through the Minkowski distance function

Belkacem Khaldi, Fouzi Harrou, Foudil Cherif, Ying Sun

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

12 Scopus citations


In this work, we study a simple collective behaviour, called aggregation, performed by a swarm of mobile robots system. We mainly proposed the Distance-Minkowski k-Nearest Neighbours (DM-KNN) as a new approach to the aggregation behaviour of simple robots swarm system. The method introduced the Minkowski distance function in computing distances between robots' neighbours. In this approach, the set k-nn members with which each robot will interact with is identified. Then an artificial viscoelastic mesh among the set members is built to perform the aggregation. When Analyzing experimental results based on ARGoS, a significant improvement in the aggregation performance of the swarm is shown compared to the classical distance-weighted k-NN aggregation approach.
Original languageEnglish (US)
Title of host publication2020 6th International Conference on Mechatronics and Robotics Engineering (ICMRE)
Number of pages5
ISBN (Print)978-1-7281-5740-5
StatePublished - 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No: OSR2019-CRG7-3800.


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