精准农业应用于通过利用数值模拟的收获操作
Federico Cheli1, Ahmed Khaled Mohamed Abdelaziz2, Stefano Arrigoni1
1Department of Mechanical Engineering, Politecnico di Milano, Via La Masa 1, 20156 Milano, Italy.
Sensors (Basel, Switzerland)
|February 24, 2024
概括
本研究引入了精密农业收获的双层控制框架,优化了收割机的操作,以减少作物损失和停机时间. 该系统有效地遵循理想条件下的路径,但需要对不平坦的地形进行调整,以防止错过的作物.
科学领域:
- 农业工程 农业工程
- 机器人和自动化机器人与自动化
- 精准农业 精准农业 精准农业
背景情况:
- 优化机组收割机运营对于最大限度地减少收获损失和运营停机时间至关重要.
- 精准农业需要先进的控制系统,以实现高效准确的收获过程.
研究的目的:
- 建议采用双层算法,为机组收割机提供全面的控制框架.
- 开发一个模拟环境来分析收获损失,时间和燃料消耗.
- 为了评估视觉引导的斯坦利横向控制器用于路径跟踪的性能.
主要方法:
- 开发了一种两层控制算法:用于收获技术的路径规划和使用视觉引导的斯坦利横向控制器的路径跟踪.
- 利用IPG-CarMaker软件创建具有挑战性的驾驶场景来模拟小麦收获.
- 实施了一个DIL框架,用于比较自动驾驶和人类驾驶.
主要成果:
- 控制器在正常现场条件下有效地遵循参考轨迹,实现零收获浪费和最小的停机时间.
- 严重的道路不规则需要重新规划参考轨迹,建议采集替代方法或头部重叠.
- 提出了采摘技术的定量和质量比较,以及地形不规则和必要的重叠之间的关系.
结论:
- 开发的控制框架在精密农业收获方面表现出有效性,特别是在理想条件下.
- 适应,如轨迹重新规划或头部重叠,是必要的导航不平坦的地形,以确保完整的作物收获.
- 拟议的DIL框架为在农业环境中评估自动驾驶系统提供了有价值的方法.
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