Development and implementation of algorithms in a population of cooperative autonomous mobile robots

Abstract

An increase in the number of mobile robot users has lead to the design and implementation of cooperative autonomous mobile robots. Autonomous robots require the ability to build maps of an unknown environment while simultaneously using these maps for navigation. The main factor in multiple mobile robots is that a team of smaller and simpler mobile robots can outperform a single, large and complex robot. The paper treats localization and map building as a joint probability, that is while robots navigate they localize and build local maps. These local maps from each robot in the team are fused into a global map at some instances during navigation. Cooperative simultaneous localization and map building (C-SLAM) implemented by Extended Kalman Filter (EKF) algorithms are proposed towards task manipulation in a multirobot set up. The article entails modelling a multiple mobile robot system, in order to understand robot population communication and cooperation within an operational environment