基于轻量化Transformer的农作物检测机器人路径规划  

Path planning of crop inspection robot based on lightweight Transformer

作　　者：李娟[1] 金志雄 Li Juan;Jin Zhixiong(Sichuan Top IT Vocational Institute,Chengdu,611743,China;University of Electronic Science and Technology of China,Chengdu,610054,China)

机构地区：[1]四川托普信息技术职业学院,成都市611743 [2]电子科技大学,成都市610054

出　　处：《中国农机化学报》2024年第9期227-233,共7页Journal of Chinese Agricultural Mechanization

基　　金：国家自然科学基金资助项目(62071096)。

摘　　要：为解决农作物检测机器人路径规划算法在复杂农田环境下精度低、速度慢等问题,设计轻量化Transformer模型,将其用于农作物检测机器人的路径规划任务中。采用余弦函数替代softmax计算,使得查询、键、值向量的计算可拆分,时间复杂度由原来的O(N2)降低到O(N)。通过四种不同聚合方式处理特征向量,确定节点权重分配。试验结果表明,基于轻量化Transformer的农作物检测机器人路径规划方法能够显著提高农作物检测机器人的效率和准确性。相比传统的规则化路径规划算法,将100规模农作物检测机器人的路径长度缩短5.91%;相比Transformer模型,推理时间缩短50%,训练时间缩短75%,为农作物检测机器人的路径规划提供一种新颖且有效的解决方案。In order to solve the problems such as low precision and slow speed of path planning algorithm of crop inspection robot in complex farmland environment,this paper designed a lightweight Transformer model and applied it to the path planning task of crop inspection robots.The cosine function was used to replace the softmax calculation,so that the computation of query,key and value vectors could be split,and the time complexity was reduced from O(N 2)to O(N).Four different aggregation methods were used to process the feature vectors and determine the node weight allocation.The experimental results showed that the path planning method of crop detection robot based on lightweight Transformer could significantly improve the efficiency and accuracy of crop detection robot.Compared with the traditional regularized path planning algorithm,it shortened the path length of 100‑scale crop detection robot by 5.91%.Compared with the Transformer model,it reduced the inference time by 50%and the training time by 75%.It provided a novel and effective solution for the path planning of crop detection robot.

关 键 词：农作物检测机器人 轻量化Transformer 强化学习 多智能体 路径规划 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] S23[自动化与计算机技术—控制科学与工程]