A bacterial colony growth framework for collaborative multi-robot localization

Abstract

In this paper the multi-robot localization problem is addressed. A new biology-inspired approach is proposed and implemented: the bacterial colony growth framework (BCGF). It takes advantage of the models of species reproduction to provide a suitable framework for carrying on the multi-hypothesis, along with proper policies for both autonomous and collaborative contexts. Collaboration among robots is obtained by exchanging sensory data and their relative distance and orientation. This information is integrated into the framework in such a way that the convergence aptitude is enhanced. Several simulations in different environments have been performed, comparing autonomous and collaborative localization, along with proper statistical analysis for performance assessment.