Monash University
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Route Optimisation for Autonomous Agricultural Sparying Robots

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thesis
posted on 2025-07-25, 09:09 authored by Qian Wan
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.