Hybrid path planning methods for complete coverage in harvesting operation scenarios

文献类型： 外文期刊

第一作者： Wang, Ning

作者： Wang, Ning;Jin, Zhiwen;Zhang, Zhao;Zhang, Man;Li, Han;Wang, Ning;Jin, Zhiwen;Wang, Tianhai;Xiao, Jianxing;Zhang, Man;Wang, Hao;Wang, Hao

作者机构：

关键词： Agricultural machinery; Complete coverage path planning; Minimum row spacing; Corner turning path model; Electronic map

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：8.9； 五年影响因子：9.3 ）

ISSN： 0168-1699

年卷期： 2025 年 231 卷

页码：

收录情况： SCI

摘要： This study addresses the challenge of autonomous navigation path planning for achieving complete coverage operations using agricultural machines within harvest operation scenarios. We proposed a hybrid method mixing nested and spiral method to solve path planning problems for convex polygonal plots during harvest operations, focusing on the development of path planning models and complete coverage path planning (CCPP) method. Based on the electronic map we built, the path planning model was constructed, which includes headland working-row connection path model and working-row traversal path model. The corner-turning path model for non-parallel work rows was proposed in the headland working-row connection path model, which has extended the applicability of different turning patterns. To achieve efficient CCPP, the improved nested method, minimum row spacing nested method (MRS-NM) was proposed. Utilizing the proposed path planning model, the hybrid path planning for harvesting operation scenarios was finally proposed, which has mixed the inner spiral and the improved nested method. Simulation tests on three groups of actual fields demonstrate that the CCPP algorithm proposed in this study fulfills the requirements of the actual harvesting process. The proposed hybrid path planning method reduces the time consumed by more than 11 % in comparison to the nested method algorithm, and the time consumed by the algorithm varies with the plot area. In the wheat harvest scenario, a complete coverage navigation experiment was carried out on three test plots. The results demonstrate that the proposed hybrid path planning method achieved a remarkable coverage rate exceeding 97 %. And it has significantly reduced the non-work path length by 36.36 m, which is an approximate 18 % reduction compared to the mixed coverage method utilizing inner spiral and reciprocating methods. The results confirm that the proposed hybrid path planning algorithm has effectively realized CCPP for convex polygonal plots, as demonstrated through trajectory acquisition experiments. This study has provided theoretical and technical foundations for achieving CCPP for convex polygonal plots during harvest operations.

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