This research addresses a real-world problem in optimising routes for automated robotic sprayers in orchard spraying. It develops mathematical models and optimisation techniques to minimise travel distance while meeting edge demand and capacity constraints across various scenarios. The solution method integrates exact and heuristic algorithms, leveraging mathematical insights into orchard layouts to enhance efficiency and solution quality. This study contributes to more sustainable and automated precision spraying operations by bridging mathematical optimisation with practical agricultural needs, improving efficiency in large-scale orchards and advancing real-world applications of optimisation in precision agriculture.
History
Campus location
Australia
Principal supervisor
Andreas Ernst
Additional supervisor 1
Rodolfo García-Flores
Additional supervisor 2
Simon Bowly
Year of Award
2025
Department, School or Centre
Mathematics
Additional Institution or Organisation
CSIRO Data61
Course
Doctor of Philosophy
Degree Type
DOCTORATE
Faculty
Faculty of Science
Rights Statement
The author retains copyright of this thesis. It must only be used for personal non-commercial research, education and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission. For further terms use the In Copyright link under the License field.