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自主机器人系统使用深度学习和关节操纵器的语义细分来修剪甜叶
Truong Thi Huong Giang1, Young-Jae Ryoo2
1Department of Information Technology, Tay Nguyen University, Buonmathuot 63161, Vietnam.
Biomimetics (Basel, Switzerland)
|March 27, 2024
概括
这项研究介绍了一种自主机器人系统,用于修剪甜叶. 基于深度学习的语义细分和一个有关节的操纵器可以实现精确的作物管理,增强农业自动化.
科学领域:
- 农业机器人农业机器人
- 计算机视觉 计算机视觉
- 深度学习 (Deep Learning) 是一种深度学习.
背景情况:
- 自动化农业任务对于效率和可持续性至关重要.
- 精准农业需要复杂的机器人系统来进行植物管理.
- 甜种植可以从自动修剪中受益,以优化产量.
研究的目的:
- 开发一种自主机器人系统,用于修剪甜的叶子.
- 为了整合语义细分,3D点云分析和修剪的操纵器控制.
- 为了证明机器人修剪在受控农业环境中的可行性.
主要方法:
- 利用基于深度学习的语义细分来识别甜植物部分.
- 从深度摄像头数据生成3D点云,用于精确的修剪位置检测.
- 实现了一个通过机器人操作系统 (ROS) 控制的关节操纵机器人.
主要成果:
- 成功地使用语义细分识别识别了甜植物的不同部分.
- 从3D点云精确检测到修剪位置和确定操纵器姿势.
- 在特定的高度范围内展示了甜叶的机器人修剪.
结论:
- 拟议的自主系统有效地整合了机器人修剪的感知和控制.
- 语义细分和3D点云分析是精确农业机器人的关键组成部分.
- 该系统为园艺实践中先进的自动化提供了基础.
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