Development of an Improved KOA Algorithm for Solving Task Allocation in Hilly Orchards With Weeding Robots
Multi-machine collaboration in agricultural machinery is a key focus in current research, with task allocation being an indispensable component. However, the current optimization objectives for task allocation in agricultural machinery are mostly confined to travel distance or time, aiming to balanc...
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IEEE
2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10910132/ |
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| author | Xiaolin Xie Hang Jin Heng Wang Man Xu Cheng Zhang Xin Jin Zhihong Zhang |
| author_facet | Xiaolin Xie Hang Jin Heng Wang Man Xu Cheng Zhang Xin Jin Zhihong Zhang |
| author_sort | Xiaolin Xie |
| collection | DOAJ |
| description | Multi-machine collaboration in agricultural machinery is a key focus in current research, with task allocation being an indispensable component. However, the current optimization objectives for task allocation in agricultural machinery are mostly confined to travel distance or time, aiming to balance task distribution. These methods are not suitable for emerging electric agricultural machinery, especially when operating in hilly areas. To address these limitations, this study proposed a task allocation method optimized for energy consumption, specifically for weeding robots in hilly orchards. Initially, drones were employed to obtain the Digital Surface Model (DSM) and orthophotos of the orchard test area. After processing the data through vegetation filtering, DEM construction, and slope analysis, slope information of the surface was derived. An electronic map of the orchard reflecting this slope information was then generated. Subsequently, the task allocation problem for weeding robots in hilly orchards was defined. A mathematical model was then established with energy consumption as the optimization objective. Finally, a Golden Kepler Optimization Algorithm (GKOA) was developed and tested through simulations using real data from the test area. The results indicated that, compared to Particle Swarm Optimization (PSO), Sparrow Search Algorithm (SSA), Whale Optimization Algorithm (WOA), and Kepler Optimization Algorithm (KOA), GKOA reduced the optimal solution cost by 10.3%, 8.2%, 7.0%, and 4.5%, respectively. This task allocation method was able to achieve the optimal task allocation plan with lower travel energy consumption costs and a higher balance in task distribution, whether for all plots in the orchard or nested plots. |
| format | Article |
| id | doaj-art-b2f2c31cbf254a038a1ec29d78ff0004 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| spelling | doaj-art-b2f2c31cbf254a038a1ec29d78ff00042025-08-20T02:56:39ZengIEEEIEEE Access2169-35362025-01-0113441844419510.1109/ACCESS.2025.354816210910132Development of an Improved KOA Algorithm for Solving Task Allocation in Hilly Orchards With Weeding RobotsXiaolin Xie0https://orcid.org/0000-0003-0111-7027Hang Jin1Heng Wang2Man Xu3Cheng Zhang4Xin Jin5Zhihong Zhang6College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, ChinaCollege of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, ChinaCollege of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, ChinaCollege of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, ChinaCollege of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, ChinaCollege of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, ChinaCollege of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, ChinaMulti-machine collaboration in agricultural machinery is a key focus in current research, with task allocation being an indispensable component. However, the current optimization objectives for task allocation in agricultural machinery are mostly confined to travel distance or time, aiming to balance task distribution. These methods are not suitable for emerging electric agricultural machinery, especially when operating in hilly areas. To address these limitations, this study proposed a task allocation method optimized for energy consumption, specifically for weeding robots in hilly orchards. Initially, drones were employed to obtain the Digital Surface Model (DSM) and orthophotos of the orchard test area. After processing the data through vegetation filtering, DEM construction, and slope analysis, slope information of the surface was derived. An electronic map of the orchard reflecting this slope information was then generated. Subsequently, the task allocation problem for weeding robots in hilly orchards was defined. A mathematical model was then established with energy consumption as the optimization objective. Finally, a Golden Kepler Optimization Algorithm (GKOA) was developed and tested through simulations using real data from the test area. The results indicated that, compared to Particle Swarm Optimization (PSO), Sparrow Search Algorithm (SSA), Whale Optimization Algorithm (WOA), and Kepler Optimization Algorithm (KOA), GKOA reduced the optimal solution cost by 10.3%, 8.2%, 7.0%, and 4.5%, respectively. This task allocation method was able to achieve the optimal task allocation plan with lower travel energy consumption costs and a higher balance in task distribution, whether for all plots in the orchard or nested plots.https://ieeexplore.ieee.org/document/10910132/Task allocationelectric agricultural machineryenergy consumptionbalance degreeslope |
| spellingShingle | Xiaolin Xie Hang Jin Heng Wang Man Xu Cheng Zhang Xin Jin Zhihong Zhang Development of an Improved KOA Algorithm for Solving Task Allocation in Hilly Orchards With Weeding Robots IEEE Access Task allocation electric agricultural machinery energy consumption balance degree slope |
| title | Development of an Improved KOA Algorithm for Solving Task Allocation in Hilly Orchards With Weeding Robots |
| title_full | Development of an Improved KOA Algorithm for Solving Task Allocation in Hilly Orchards With Weeding Robots |
| title_fullStr | Development of an Improved KOA Algorithm for Solving Task Allocation in Hilly Orchards With Weeding Robots |
| title_full_unstemmed | Development of an Improved KOA Algorithm for Solving Task Allocation in Hilly Orchards With Weeding Robots |
| title_short | Development of an Improved KOA Algorithm for Solving Task Allocation in Hilly Orchards With Weeding Robots |
| title_sort | development of an improved koa algorithm for solving task allocation in hilly orchards with weeding robots |
| topic | Task allocation electric agricultural machinery energy consumption balance degree slope |
| url | https://ieeexplore.ieee.org/document/10910132/ |
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