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Study on Path Planning in Cotton Fields Based on Prior Navigation Information

文献类型: 外文期刊

作者: Wang, Meng 1 ; Niu, Changhe 3 ; Wang, Zifan 1 ; Jiang, Yongxin 3 ; Jian, Jianming 1 ; Tang, Xiuying 1 ;

作者机构: 1.China Agr Univ, Coll Engn, Beijing 100083, Peoples R China

2.Xinjiang Inst Engn, Sch Mech & Elect Engn, Urumqi 830023, Peoples R China

3.Xinjiang Acad Agr Sci, Res Inst Agr Mechanizat, Urumqi 830091, Peoples R China

关键词: agricultural machinery path planning; sowing navigation information; turnaround; obstacle avoidance; prior semantic map

期刊名称:AGRICULTURE-BASEL ( 影响因子:3.6; 五年影响因子:3.8 )

ISSN:

年卷期: 2024 年 14 卷 11 期

页码:

收录情况: SCI

摘要: Aiming at the operation scenario of existing crop coverage and the need for precise row alignment, the sowing prior navigation information of cotton fields in Xinjiang was used as the basis for the study of path planning for subsequent operations to improve the planning quality and operation accuracy. Firstly, the characteristics of typical turnaround methods were analyzed, the turnaround strategy for dividing planning units was proposed, and the horizontal and vertical operation connection methods were put forward. Secondly, the obstacle avoidance strategies were determined according to the traits of obstacles. The circular arc-linear and cubic spline curve obstacle avoidance path generation methods were proposed. Considering the dual attributes of walking and the operation of agricultural machinery, four kinds of operation semantic points were embedded into the path. Finally, path generation software was designed. The simulation and field test results indicated that the operation coverage ratio CR >= 98.21% positively correlated with the plot area and the operation distance ratio DR >= 86.89% when non-essential reversing and obstacles were ignored. CR and DR were negatively correlated with the number of obstacles when considering obstacles. When considering non-essential reversing, the full coverage of operating rows could be achieved, but DR would be reduced correspondingly.

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