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ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Sustainable and Intelligent Phytoprotection
Volume 15 - 2024 |
doi: 10.3389/fpls.2024.1440234
This article is part of the Research Topic Advanced Methods, Equipment and Platforms in Precision Field Crops Protection, Volume II View all articles
An Integrated Framework for UAV-Based Precision Plant Protection in Complex Terrain: the ACHAGA Solution for Multi-Tea Fields
Provisionally accepted- 1 College of Horticulture and Forestry Sciences, Tarim University, Aral, Xinjiang Uyghur Region, China
- 2 Xinjiang Production & Construction Corps Key Laboratory of Facility Agriculture, Aral, China
- 3 School of Engineering, Anhui Agricultural University, Hefei, Anhui Province, China
UAV-based plant protection represents an efficient, energy-saving agricultural technology with significant potential to enhance tea production. However, the complex terrain of hilly and mountainous tea fields, coupled with the limited endurance of UAVs, presents substantial challenges for efficient route planning. This study introduces a novel methodological framework for UAV-based precision plant protection across multiple tea fields, addressing the difficulties in planning the shortest routes and optimal flights for UAVs constrained by their endurance. The framework employs a hyperbolic genetic annealing algorithm (ACHAGA) to optimize UAV plant protection routes with the objectives of minimizing flight distance, reducing the number of turns, and enhancing route stability. The method involves two primary steps: cluster partitioning and sortie allocation for multiple tea fields based on UAV range capabilities, followed by refining the UAV's flight path using a combination of hyperbolic genetic and simulated annealing algorithms with an adaptive temperature control mechanism. Simulation experiments and UAV route validation tests confirm the effectiveness of ACHAGA. The algorithm consistently identified optimal solutions within an average of 40 iterations, demonstrating robust global search capabilities and stability. It achieved an average reduction of 45.75 iterations and 1811.93 meters in the optimal route, with lower variation coefficients and extreme deviations across repeated simulations. ACHAGA significantly outperforms these algorithms, GA, GA-ACO, AFSA and BSO, which are also heuristic search strategies, in the multi-tea field route scheduling problem, reducing the optimal routes by 4904.82 m, 926.07 m, 3803.96 m and 800.11 m, respectively. Field tests revealed that ACHAGA reduced actual flight routes by 791.9 meters and 359.6 meters compared to manual and brainstorming-based planning methods, respectively. Additionally, the algorithm reduced flight scheduling distance and the number of turns by 11 compared to manual planning. This study provides a theoretical and technical foundation for managing large-scale tea plantations in challenging landscapes and serves as a reference for UAV precision operation planning in complex environments.
Keywords: UAV-based plant protection, multi-tea field plant protection, Unmanned Aerial Vehicle, replenishment -scheduling optimisation, scheduling route planning
Received: 29 May 2024; Accepted: 27 Aug 2024.
Copyright: © 2024 Zhang, Liu and Du. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Pengyang Zhang, College of Horticulture and Forestry Sciences, Tarim University, Aral, 843300, Xinjiang Uyghur Region, China
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