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温室胡培养中的机器人授粉关键技术的进展和前景:一篇综述
Minqiu Kuang1,2, Xiaojian Li1, Fangping Xie1,3
1School of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China.
Frontiers in plant science
|March 16, 2026
概括
智能农业中的机器人授粉在精确的花朵检测和最终效应器设计方面面临着挑战. 未来的系统需要强大的人工智能,大数据集和适应性控制,以实现高效,非破坏性的授粉.
科学领域:
- 农业工程 农业工程
- 机器人技术 机器人技术 机器人技术
- 计算机视觉 计算机视觉
背景情况:
- 智能农业越来越依赖于自动化,机器人授粉是一个关键领域.
- 现有的机器人授粉系统在现实世界的整合中面临挑战,特别是在感知,决策和执行方面.
- 温室机器人授粉需要在目标识别,路径规划和运动控制方面取得进展.
研究的目的:
- 系统地审查机器人授粉技术的进展.
- 确定温室机器人授粉的核心技术挑战,重点关注目标检测,终端效应器设计和运动控制.
- 评估自动化授粉系统的最新情况和未来方向,特别是对于植物.
主要方法:
- 对机器人授粉的最新进展进行系统的文献综述.
- 分析目标检测和姿势估计,终端效应器设计以及带有运动控制的授粉策略的技术问题.
- 全球自动授粉研究,方法和系统案例的分类.
主要成果:
- 目前的机器人授粉受到不精确的花朵检测/姿势估计和低于最佳的终端效应器设计的阻碍.
- 检测算法的准确性和稳定性,终端效应器结构和控制战略优化是分析的关键领域.
- 现有系统在动态环境条件下需要更强大的决策.
结论:
- 未来的发展必须专注于大规模的花数据集和可适应的检测算法,以实现高精度的识别.
- 集成感知驱动的执行和实时分析的深度学习的层次架构至关重要.
- 实施触觉反和多式运动控制将使精确的,非破坏性的授粉能够适合等特定作物.
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