基于3D SLAM和点云定位融合的果园导航方法的研究
Ye Xia1,2,3, Xiaohui Lei1,2, Jian Pan1,2
1Institute of Agricultural Facilities and Equipment, Jiangsu Academy of Agricultural Sciences, Nanjing, China.
Frontiers in plant science
|July 12, 2023
概括
本研究介绍了用于智能果园的3D LiDAR导航系统,克服了传统方法的局限性. 该系统实现了自动驾驶汽车的厘米级精度,提高了精准农业.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 农业工程 农业工程
- 计算机视觉 计算机视觉
背景情况:
- 智能果园导航需要高精度,由于天花板遮蔽,GNSS/2D LiDAR的不可靠性受到挑战.
- 传统方法在复杂的果园环境中与有限的感官信息作斗争.
研究的目的:
- 提出和验证基于3D LiDAR的导航方法,用于网格式果园.
- 为了提高自动驾驶汽车定位和路径跟踪准确性,在果园里.
主要方法:
- 使用3D LiDAR和3D同时定位和映射 (SLAM) 来获取点云数据.
- 通过使用点云库 (PCL) 来提取过的点云来提取格结构.
- 实现了传感器融合,包括实时动力学 (RTK) 和正常分布转换 (NDT) 以实现精确的定位.
- 通过手动创建矢量地图和用于导航的纯路径跟踪来开发路径规划.
主要成果:
- NDT SLAM实现了厘米级准确度 (5厘米) 的低变化 (<2%).
- 导航系统表现出高准确度 (在1°以内,SD<0.6°) 和侧向定位控制 (在5cm以内,SD<2cm) 在1.0m/s.
- 在Y-trellis梨园环境中验证了性能.
结论:
- 拟议的3D LiDAR导航系统为网格式果园中的自动驾驶车辆提供了高精度和可靠性.
- 该系统是可定制的,适用于诸如自主杀虫剂喷雾器等应用,推进智能农业.
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