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Multi-robot coverage path planning using hexagonal segmentation for geophysical surveys

Published online by Cambridge University Press:  15 April 2018

Héctor Azpúrua*
Affiliation:
Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG 31270-901, Brazil. E-mails: doug@dcc.ufmg.br, mario@dcc.ufmg.br Instituto Tecnológico Vale, Ouro Preto, MG 35400-000, Brazil. E-mail: gustavo.medeiros.freitas@itv.org
Gustavo M. Freitas
Affiliation:
Instituto Tecnológico Vale, Ouro Preto, MG 35400-000, Brazil. E-mail: gustavo.medeiros.freitas@itv.org
Douglas G. Macharet
Affiliation:
Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG 31270-901, Brazil. E-mails: doug@dcc.ufmg.br, mario@dcc.ufmg.br
Mario F. M. Campos
Affiliation:
Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG 31270-901, Brazil. E-mails: doug@dcc.ufmg.br, mario@dcc.ufmg.br
*
*Corresponding author. E-mail: hector.azpurua@itv.org
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The field of robotics has received significant attention in our society due to the extensive use of robotic manipulators; however, recent advances in the research on autonomous vehicles have demonstrated a broader range of applications, such as exploration, surveillance, and environmental monitoring. In this sense, the problem of efficiently building a model of the environment using cooperative mobile robots is critical. Finding routes that are either length or time-optimized is essential for real-world applications of small autonomous robots. This paper addresses the problem of multi-robot area coverage path planning for geophysical surveys. Such surveys have many applications in mineral exploration, geology, archeology, and oceanography, among other fields. We propose a methodology that segments the environment into hexagonal cells and allocates groups of robots to different clusters of non-obstructed cells to acquire data. Cells can be covered by lawnmower, square or centroid patterns with specific configurations to address the constraints of magneto-metric surveys. Several trials were executed in a simulated environment, and a statistical investigation of the results is provided. We also report the results of experiments that were performed with real Unmanned Aerial Vehicles in an outdoor setting.

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Copyright © Cambridge University Press 2018