Ma, Na and Mantri, Anil and Bough, Graham and Patnaik, Ayush and Yadav, Siddhesh and Nansen, Christian and Kong, Zhaodan (2022) Data-driven vermiculite distribution modelling for UAV-based precision pest management. Frontiers in Robotics and AI, 9. ISSN 2296-9144
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Abstract
In recent decades, unmanned aerial vehicles (UAVs) have gained considerable popularity in the agricultural sector, in which UAV-based actuation is used to spray pesticides and release biological control agents. A key challenge in such UAV-based actuation is to account for wind speed and UAV flight parameters to maximize precision-delivery of pesticides and biological control agents. This paper describes a data-driven framework to predict density distribution patterns of vermiculite dispensed from a hovering UAV as a function of UAV’s movement state, wind condition, and dispenser setting. The model, derived by our proposed learning algorithm, is able to accurately predict the vermiculite distribution pattern evaluated in terms of both training and test data. Our framework and algorithm can be easily translated to other precision pest management problems with different UAVs and dispensers and for difference pesticides and crops. Moreover, our model, due to its simple analytical form, can be incorporated into the design of a controller that can optimize autonomous UAV delivery of desired amount of predatory mites to multiple target locations.
Item Type: | Article |
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Subjects: | Digital Academic Press > Mathematical Science |
Depositing User: | Unnamed user with email support@digiacademicpress.org |
Date Deposited: | 21 Jun 2023 06:24 |
Last Modified: | 05 Jun 2024 09:59 |
URI: | http://science.researchersasian.com/id/eprint/1543 |