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研究基于主动选-卡尔曼选的联合定位算法.

Xiao Zhang1, Yuting Fu1, Jie Li1

  • 1College of Engineering, China Agricultural University, Beijing 100083, China.

Sensors (Basel, Switzerland)
|April 13, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种用于农业机器人的活跃过-卡尔曼过算法. 与传统方法相比,它通过减少定位错误显著改善了精确的导航.

关键词:
卡尔曼过器可以过.主动过活动过.组合定位系统 (combined positioning) 是一种联合定位系统.动态定位定位 动态定位定位静态定位定位 静态定位定位

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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
  • 地理学工程 工程地质学

背景情况:

  • 高精度导航对于农业机器人系统至关重要.
  • 全球导航卫星系统 (GNSS) 数据可能很复杂,包含漂移点.
  • 现有的定位方法可能无法满足智能农业的准确性要求.

研究的目的:

  • 为农业机器人开发一种新的数据过和联合定位方法.
  • 提高实时定位采集的准确性和可靠性.
  • 为了减少农业机器人导航系统的定位错误.

主要方法:

  • 为数据过提出了一个主动选模型.
  • 开发了一个主动过-卡尔曼过算法.
  • 从GNSS数据中删除或替换动态和静态定位漂移点.

主要成果:

  • 减少了沿直线的最大距离偏差,从0.145米减少到0.055米.
  • 缩小了沿曲线的最大距离偏差,从0.184m到0.0640m.
  • 与传统的卡尔曼波器方法相比,定位错误明显减少.

结论:

  • 主动过-卡尔曼过算法提高了农业机器人的定位准确度.
  • 这种方法有助于在智能农业中推进智能导航.
  • 改善定位对于农业机器人的广泛采用至关重要.