视觉和2D LiDAR基于融合的导航线提取用于在密集的石榴果园中的自动农业机器人
Zhikang Shi1, Ziwen Bai1, Kechuan Yi1
1College of Intelligent Manufacturing, Anhui Science and Technology University, Chuzhou 239000, China.
Sensors (Basel, Switzerland)
|September 13, 2025
概括
本研究介绍了一种视觉和LiDAR融合方法,用于在石榴果园中精确地提取导航线. 这种方法显著提高了果园机器人的自主导航精度.
科学领域:
- 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
- 农业工程 农业工程
背景情况:
- 传统的单传感器导航方法在密集的果园环境中缺乏准确性.
- 石榴果园对自主机器人导航提出了独特的挑战,因为种植密集.
研究的目的:
- 开发一种强大的视觉和基于LiDAR融合的方法,用于在石榴果园中准确地提取导航线.
- 为了提高自主导航系统的精度和可靠性,用于果园操作.
主要方法:
- 集成YOLOv8-ResCBAM用于高精度的石榴树干检测.
- 一个新的反射射线投影算法,用于有效的视觉和LiDAR数据融合.
- 以几何约束增强的RANSAC算法和卡尔曼过用于稳定的导航线装配.
主要成果:
- 将横向导航的平均误差降低到5.2厘米.
- 实现了6.6厘米的平均横向误差 根平均平方 (RMS).
- 在实地实验中获得了95.4%的高导航成功率.
结论:
- 拟议的视觉和2D LiDAR融合方法显著优于单传感器和语义细分方法.
- 这种基于融合的导航策略为复杂的果园环境中的自主导航提供了可行的解决方案.
- 该方法为通过增强机器人能力推进精密农业提供了基础.
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