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

6 Scopus citations

Abstract

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)
PublisherIEEE
Pages87-91
Number of pages5
ISBN (Print)978-1-7281-5740-5
DOIs
StatePublished - 2020

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