To identify whether the actual work trajectory of workers in the factory meets the predetermined work trajectory requirements, we proposed an efficient and accurate work trajectory similarity matching method. We comprehensively considered the similarity between the actual work track and the predetermined track from the two characteristics of track angle and track distance. Among them, the similarity of track rotation angle is calculated using the improved longest common subsequence algorithm, and the similarity of track distance is calculated using the improved dynamic time warping (DTW) algorithm. Then the results of the similarity calculation of these two features are weighted. Finally, the weighted results are used to evaluate the similarity between the actual work track and the predetermined track, so as to judge whether the actual work track meets the requirements of the predetermined track. Experimental data show that the trajectory similarity matching algorithm in this paper has higher accuracy and efficiency than traditional DTW and other algorithms, and has higher ability to resist the interference of trajectory point evacuation than traditional DTW and other algorithms.

中文翻译：

---

基于工作轨迹相似度的匹配方法

为了识别工厂工人的实际工作轨迹是否满足预定的工作轨迹要求，我们提出了一种高效准确的工作轨迹相似度匹配方法。我们从轨道角度和轨道距离两个特征综合考虑了实际工作轨道与预定轨道的相似性。其中，航迹旋转角度相似度采用改进的最长公共子序列算法计算，航迹距离相似度采用改进的动态时间规整(DTW)算法计算。然后对这两个特征的相似度计算结果进行加权。最后，将加权结果用于评估实际工作轨迹与预定轨迹的相似度，从而判断实际工作轨迹是否符合预定轨迹的要求。实验数据表明，本文的轨迹相似度匹配算法比传统的DTW等算法具有更高的精度和效率，比传统的DTW等算法具有更高的抗轨迹点疏散干扰的能力。