Improving robots swarm aggregation performance through the Minkowski distance function

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.