Multiple in-field operations, including seeding and weeding, were closely observed, measured, and analyzed in comparison to conventional machinery. In addition, Mahdi Vahdanjoo formulated an optimization model specifically tailored to enhance the efficiency of the robot's in-field operation across different scenarios. This model considered various factors such as crop health, as determined by the NDVI index, as well as environmental impact, including CO2 emissions and the risk of soil compaction within a specified field sample. Furthermore, Mahdi Vahdanjoo pioneered the development of a predictive model that utilizes machine learning techniques to estimate the fuel consumption of the agricultural robot. To further enhance the analysis process, a simulation model was created to simulate the robot's operation under various scenarios.

The PhD study was completed at the Department of Agroecology, Faculty of Technical Sciences, Aarhus University.

This summary was prepared by the PhD student.

Time: Thursday, 26 October 2023 at 13:00.
Place: AU Flakkebjerg
Title of PhD thesis: Operational, Economic, and Environmental Assessment of an Agricultural Robot

Contact information: Mahdi Vahdanjoo, e-mail: mahdi.vahdanjoo@agro.au.dk, tel.: +45 50249037

Members of the assessment committee:

Professor Ole Ravn, Department of Electrical and Photonics Engineering, DTU, Denmark

Prof. Dr.-Ing. Timo Oksanen, TUM School of Life Sciences, Technical University of Munich, Germany

Senior researcher Henrik Skovgård, Department of Agroecology, Aarhus University, Denmark

Main supervisor:
Associate Professor René Gislum, Department of Agroecology, Aarhus University, Denmark

Co-supervisor:
Professor Claus Aage Grøn Sørensen, Department of Electrical and Computer Engineering, Aarhus University, Denmark

Language: The Ph.D. dissertation will be defended in English

The defense is public.
The PhD thesis is available for reading at the Graduate School of Technical Sciences/GSTS,

Jens Baggesens Vej 53, building 5221, 8200 Aarhus N.