戴阳, 姚宇青, 郑汉丰, 韦波, 杨昱皞, 王永进, 张禹. 基于三次B样条曲线与动态窗口算法的桁杆轨迹规划[J]. 南方水产科学, 2023, 19(2): 116-123. DOI: 10.12131/20220048
引用本文: 戴阳, 姚宇青, 郑汉丰, 韦波, 杨昱皞, 王永进, 张禹. 基于三次B样条曲线与动态窗口算法的桁杆轨迹规划[J]. 南方水产科学, 2023, 19(2): 116-123. DOI: 10.12131/20220048
DAI Yang, YAO Yuqing, ZHENG Hanfeng, WEI Bo, YANG Yuhao, WANG Yongjin, ZHANG Yu. Truss rod trajectory planning based on cubic B-spline curve and Dynamic Window Algorithm[J]. South China Fisheries Science, 2023, 19(2): 116-123. DOI: 10.12131/20220048
Citation: DAI Yang, YAO Yuqing, ZHENG Hanfeng, WEI Bo, YANG Yuhao, WANG Yongjin, ZHANG Yu. Truss rod trajectory planning based on cubic B-spline curve and Dynamic Window Algorithm[J]. South China Fisheries Science, 2023, 19(2): 116-123. DOI: 10.12131/20220048

基于三次B样条曲线与动态窗口算法的桁杆轨迹规划

Truss rod trajectory planning based on cubic B-spline curve and Dynamic Window Algorithm

  • 摘要: 针对当前中国南极磷虾 (Euphausia superba) 捕捞自动化水平较低、人工观察探渔仪图像确定捕捞深度易产生误差等问题,提出一种基于南极磷虾声呐设备元数据的动力桁杆轨迹规划方法。首先解析水声学仪器EK80科学回声探测仪传回的数据,得到磷虾在不同深度下的目标强度,用统计学方法确定磷虾在该深度下的资源量,以此得到每个水平距离 (X) 对应的磷虾最密集的深度 (Y),再利用三次B样条曲线和动态窗口算法分别进行全局和局部路径规划,规划路线通过这些磷虾最密集的深度。结果显示,规划路径全长1 054 m,总用时614 s,动态窗口算法跟踪的最大偏离距离仅为3.3 m,小于预计的最大偏移距离 (5 m)。所提出的方法具有以下优点:1) 有效避免人工判断资源量深度产生误差而对捕捞量造成影响,提高捕捞效率;2) 实现自动规划捕捞效益最佳的桁杆前进路线。

     

    Abstract: In order to solve the problems such as the current low level of automation in the fishing of Antarctic krills (Euphausia superba) in China, and the error in determining the fishing depth by manually observing the fish detector image, we proposed a dynamic truss trajectory planning method based on the metadata of Antarctic krill sonar equipment. First, we analyzed the data sent back by the underwater acoustic instrument EK80 scientific echo sounder, obtained the target intensity of krills at different depths, and used statistical methods to determine the krills resources at this depth, so as to get the densest depth (Y) of krills corresponding to each horizontal distance (X). Then we used cubic B-spline curve and Dynamic Window Algorithm to carry out the global path planning and local path planning. The planned route passed through the densest depth of these krills. The results show that the total length of the planned path was 1 054 m, and the total time was 614 s. The maximum deviation distance tracked by the Dynamic Window Algorithm was only 3.3 m, which was less than the expected maximum deviation distance of 5 m. The proposed method can: 1) Avoid the impact of artificial judgment of resource depth on the fishing volume effectively, and improve the fishing efficiency. 2) Realize the automatic planning of the truss forward route with the best fishing efficiency.

     

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