The purpose of this paper is to develop a methodology for detecting tree trunks for autonomous agricultural applications performed using mobile robots.
The system is constructed by following the principles of Voronoi diagram method which is one of the machine learning algorithms used by the robotics, mechatronics and automation researchers.
To analyze the accuracy and performance and to make verification and evaluation, both simulation and experimental studies are conducted. The results indicate that the tree trunk detection system developed using Voronoi diagram method can be able to detect tree trunks with high precision.
A novel solution technique to detect tree trunks is proposed. The adaptation of Voronoi diagram method in an agricultural (orchard) task is presented.
The author would like to thank the Engineering Faculty of Bulent Ecevit University (Zonguldak, Turkey) for its financial supports in this study. He would also like to thank the research project (BAP-2016-77654622-02) supported by the Bulent Ecevit University.
Bayar, G. (2017), "Development of a Voronoi diagram based tree trunk detection system for mobile robots used in agricultural applications", Industrial Robot, Vol. 44 No. 4, pp. 521-531. https://doi.org/10.1108/IR-11-2016-0304
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