Democratic multi-robot exploration: New method to compute Particle Swarm Optimizations' global best parameter

Abstract

In multi-robot exploration operation, each robot has to continuously decide which place to move next, after exploring their current location. In this paper we use the extended version of Particle Swarm Optimization (PSO) to robotic application, which is referred to as Robotic Particle Swarm Optimization (RPSO), a technique to compute robots' new location. To better adapt this technique to the collective exploration problem, and maximize the exploring area, we used a new method for computing PSOs' global best parameter. Experiment results obtained in a simulated environment show that our new method of computing PSOs' global best parameter increase the explored area.