基于三维激光雷达的履带农业机器人室外定位方法*

doi:10.12398/j.issn.2096-7217.2020.02.001

智能化农业装备学报（中英文） ›› 2020, Vol. 1 ›› Issue (2): 1-10.DOI: 10.12398/j.issn.2096-7217.2020.02.001

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基于三维激光雷达的履带农业机器人室外定位方法^*

王凯^1,2, 周俊^1,2, Opiyo Samwel^1,2, 张保华^1,2, 张文海^1,2

1.南京农业大学工学院,南京市,210031;
2.江苏省智能化农业装备重点实验室,南京市, 210031

收稿日期:2020-09-30 出版日期:2020-11-15 发布日期:2021-11-30
通讯作者: 周俊,男,博士,教授,博导;研究方向为农业机器人、智能化农业装备。E-mail: zhoujun@njau.edu.cn
作者简介:王凯,男,博士研究生;研究方向为农业机器人导航。E-mail: wk65010@163.com
基金资助:
*江苏省重点研发项目(BE2017370)

Outdoor localization of agricultural tracked robots based on 3D lidar^*

Kai Wang^1,2, Jun Zhou^1,2, Opiyo Samwel^1,2, Baohua Zhang^1,2, Wenhai Zhang^1,2

1. College of Engineering, Nanjing Agricultural University, Nanjing, 210031, China;
2. Jiangsu Province Key Laboratory of Intelligent Agricultural Equipment, Nanjing, 210031, China

Received:2020-09-30 Online:2020-11-15 Published:2021-11-30
Contact: Jun Zhou, Doctor, Professor, Doctoral supervisor, research direction: agricultural robot and intelligent agricultural equipment. E-mail: zhoujun@njau.edu.cn
About author:Kai Wang, Doctoral candidate, research direction: agricultural robot navigation. E-mail: wk65010@163.com
Supported by:
*Key Research & Development Plan of Jiangsu Province (BE2017370)

摘要/Abstract

摘要： 针对履带农业机器人室外自主导航,本文提出了一种基于三维激光雷达的定位方法。首先,采用lidar_IMU紧耦合里程计与图优化算法建立导航区域特征点的先验地图。其次,为确保机器人能够在先验地图上的任意位置进行定位,将卫星定位信号作为索引信息导入点云地图。最后,采用轻量级激光里程计算法与先验地图进行匹配,计算机器人位于先验地图的姿态信息。同时,为了减少计算量将非线性优化区域限定在栅格化的小地图中。借助机器人携带的GNSS对系统进行了测试,当机器人运动速度1.0 m/s时,最大定位误差小于0.26 m,平均定位误差小于0.125 m,实验过程中没有出现定位失败的情况,可以满足履带农业机器人室外导航的定位需求。

关键词: lidar_IMU, 紧耦合里程计, 先验地图, 室外定位

Abstract: To realize the outdoor autonomous navigation of tracked robots, this paper proposes a localization method based on 3D lidar. First, lidar-IMU tightly coupled odometry and pose-graph optimization algorithms are used to establish a priori maps of the navigation area feature points. Second, to ensure that the robot can locate any position on the prior map, the satellite positioning information after latitude and longitude conversion is introduced into the point-cloud map information. Finally, the design uses the lightweight lidar odometry method to match the prior map to calculate the current pose of the robot. At the same time, to reduce the number of calculations, the nonlinear optimization area is limited to a rasterized small map. We use the GNSS carried by the robot to evaluate the algorithm in this paper: the maximum positioning error less than 0.26 m when the normal speed of the robot is 1.0 m/s, and the average positioning error less than 0.125 m. No localization failures occurred during the experiment, and the test results are good enough to meet the localization requirements of the tracked robot for outdoor navigation.

Key words: lidar_IMU, tightly coupled odometry, prior map, outdoor localization

中图分类号:

王凯, 周俊, Opiyo Samwel, 张保华, 张文海. 基于三维激光雷达的履带农业机器人室外定位方法^*[J]. 智能化农业装备学报（中英文）, 2020, 1(2): 1-10.

Kai Wang, Jun Zhou, Opiyo Samwel, Baohua Zhang, Wenhai Zhang. Outdoor localization of agricultural tracked robots based on 3D lidar^*[J]. Journal of Intelligent Agricultural Mechanization, 2020, 1(2): 1-10.

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基于三维激光雷达的履带农业机器人室外定位方法^*

Outdoor localization of agricultural tracked robots based on 3D lidar^*

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基于三维激光雷达的履带农业机器人室外定位方法*

Outdoor localization of agricultural tracked robots based on 3D lidar*

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基于三维激光雷达的履带农业机器人室外定位方法^*

Outdoor localization of agricultural tracked robots based on 3D lidar^*