摘要
农业自动化技术的持续进步,果实采摘机器人在提升农业生产效率方面扮演着愈发关键的角色,将成为推动农业现代化发展的重要力量。然而,在实际采摘作业场景中,复杂多变的环境因素带来了诸多挑战。光照条件的不稳定、果实间相互遮挡以及机器人自身定位精度受限等,均导致果实采摘点的空间位置出现误差,这极大地影响了采摘的准确性与效率,成为制约果实采摘机器人广泛应用的瓶颈。针对这一问题,提出了一种基于支持向量机(support vector machine,SVM)的果实采摘点空间位置误差补偿机制。该机制通过构建SVM模型,对采摘过程中的空间位置误差进行预测和补偿,从而提高采摘机器人的定位精度和采摘成功率。实验结果表明,此补偿机制切实可行,能够有效降低果实采摘点的空间位置误差。
With continuous advancements in agricultural automation technology,fruit-picking robots are playing an increasingly vital role in boosting agricultural productivity,emerging as a key driver of agricultural modernization.However,in real-world harvesting scenarios,complex environmental factors present significant challenges.Unstable lighting conditions,fruit shading,and limited positioning accuracy of the robots all lead to spatial positioning errors at picking points,severely impacting harvesting precision and efficiency.These issues become a major bottleneck hindering the widespread adoption of fruit-picking robots.For this problem,this paper proposes a spatial position error compensation mechanism based on support vector machine(SVM).This mechanism constructs the SVM model to predict and compensate the spatial position error in the picking process,so as to improve the positioning accuracy and picking success rate of the picking robot.The experimental results show that the compensation mechanism is feasible and can effectively reduce the spatial location error of fruit picking point.
作者
陈科尹
姚勇
CHEN Keyin;YAO Yong(School of Physics and Electronic Engineering,Jiaying University,Meizhou 514015,Guangdong,China)
出处
《自动化技术与应用》
2026年第4期17-19,128,共4页
Techniques of Automation and Applications
基金
国家自然科学基金(61863011)
广东省攀登计划重点项目(pdjh2022a0480)
广东省普通高校特色创新项目(2020KTSCX142)。
关键词
支持向量机
果实采摘
空间位置误差
补偿机制
support vector machine
fruit picking
spatial position error
compensation mechanism
