基维果园移动机器人的综合定位系统基于UWB/LiDAR/ODOM
Liangsheng Jia1, Yinchu Wang1, Li Ma1
1College of Mechanical and Electrical Engineering, Northwest A&F University, Xianyang 712100, China.
Sensors (Basel, Switzerland)
|September 9, 2023
概括
这项研究介绍了一种使用超宽带 (UWB),LiDAR和测距的集成定位系统,用于基维果园中的移动机器人. 该方法在具有挑战性的信号环境中显著提高了机器人定位精度.
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
- 传感器融合式传感器
背景情况:
- 农业中的移动机器人需要精确的定位.
- 梯形果园对机器人定位提出了独特的挑战,包括弱信号环境.
- 现有的定位方法往往缺乏复杂的农业任务所需的准确性.
研究的目的:
- 开发和评估一个集成的户外定位方法,用于移动机器人在状木果园.
- 通过传感器融合,在弱信号环境中提高定位准确性.
- 提高农业机器人的可靠性和性能.
主要方法:
- 实施了使用卡尔曼波器 (KF) 进行超宽带 (UWB) 定位的动态错误校正策略.
- 采用颗粒过器 (PF) 来融合UWB,光探测和距离测量 (LiDAR) 和距离测量 (ODOM) 测量.
- 使用扩展的卡尔曼波器 (EKF) 来合并预测 (ODOM) 和测量 (UWB/LiDAR/PF) 值用于机器人姿势估计.
主要成果:
- 综合的UWB/ODOM/LiDAR方法在模拟中实现了0.076米的平均横向误差和0.098米的RMSE.
- 现场测试显示,与独立的UWB相比,定位精度有64.8%的改善.
- 拟议的方法优于基于UWB的KF (13.8%的改进) 和LiDAR/ODOM (38.3%的改进) 综合方法.
结论:
- 拟议的综合定位方法证明了移动机器人在状基维果园中的卓越性能.
- 传感器融合方法有效地解决了弱信号环境的挑战.
- 这项技术对各种各样的果园环境中的各种农业机器人具有潜在的应用性.
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