Simulation of a System Architecture for Cooperative Robotic Cleaning

Abstract

The increase of the use of Autonomous Vehicles in different types of environments leads to an improvement of the Localization and Navigation algorithms. The goal is to increase the levels of efficiency, security and robustness of the system, minimizing the tasks completion time.

The application of cleaning robots in domestic environments have several advantages however some improvements should be performed in order to develop a robust system. Also in large spaces one robot doesn’t achieve the desired performance in terms of robustness to faults and efficiency in the cleaning process. Considering a fleet of autonomous robots, this process could be improved. The purpose of our paper is the presentation of an architecture for management a fleet of cleaning robots, considering a complete coverage path planning for large and structured environments. Compartments are found in a grid-like decomposition and an area coverage strategy are evolved (optimized) by using Genetic Algorithms. The Task allocation module is based on Auctions strategy, thus obtaining cooperation under dynamic constraints in complex environments. The case study optimizes the number of robots involved in the cooperative cleaning of a full building in the campus, based on its real architectural plans.