CAMINHOS DE COBERTURA ADAPTÁVEIS PARA ROBOS ASPIRADORES

Abstract

A robot vacuum cleaner can have many advantages for the routine of people who are usually busy. For its functionality, it is necessary that the path taken by the robot covers the entire surface available for cleaning, known in the literature as path coverage problem. In this work, the robot vacuum cleaner does not have prior knowledge of the area, it must adapt to the architecture and furniture of the house through sensors and it aims a shorter time to clean the entire space. We propose algorithms capable of performing a coverage path with efficient response to furniture and obstacles, through minipaths, where the robot generates several possible paths around it according to its sensors, promoting adaptability to the path of the robot vacuum cleaner. Later, with the knowledge of the complete area, paths are improved by genetic algorithms and Fix and optimize approaches. The proposed algorithms are compared to the path coverage algorithms from the literature for a set of instances. The proposed strategy performed well compared to literature approaches.