机器学习在采摘机器人中的应用与挑战
Applications and Challenges of Machine Learning in Picking Robots
王佳虹1
作者信息
- 1. 杭州乔戈里科技有限公司 浙江杭州 310051
- 折叠
摘要
技术发展推动机器学习成为自动化与智能化系统的核心技术,机器学习在农业采摘机器人上的广泛应用显示出其巨大的发展潜力与面临的挑战.归纳了机器学习在采摘机器人中应用的现状,讨论遇到的难题,并对未来的发展趋势进行预测.详细探讨了机器学习在图像识别、决策过程和自适应学习方面的实际运用,为采摘机器人的进一步优化与创新提供理论依据和操作指南.
Abstract
The development of technology has propelled machine learning to become the core technology in auto-mation and intelligent systems.The widespread application of machine learning in agricultural picking robots high-lights its huge potential for developement and the challenges it faces.In this paper,the current state of machine learning applications in picking robots is summarized,the challenges encountered are discussed,and future develop-ment trends are predicted.The practical applications of machine learning in visual recognition,decision-making processes,and adaptive learning are discussed in detail,providing theoretical foundations and operational guidelines for the further optimization and innovation of picking robots.
关键词
机器学习/采摘机器人/视觉识别/技术挑战Key words
Machine learning/Picking robot/Visual recognition/Technical challenge引用本文复制引用
基金项目
浙江省重点研发计划(2019C02029)
出版年
2024
NETL
NSTL
万方数据