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智能化农业装备学报（中英文）

智能化农业装备学报（中英文） ›› 2022, Vol. 3 ›› Issue (2): 64-70.DOI: 10.12398/j.issn.2096-7217.2022.02.008

• • 上一篇    

基于超声波传感器的巡检机器人导航纠偏研究

张磊1，刘义亭1, 2*，陈光明3, 4，李佩娟1   

  1. 1. 南京工程学院，江苏南京，211167； 2. 东南大学，江苏南京，210096； 3. 南京农业大学，江苏南京，210031；  4. 江苏省智能化农业装备重点实验室，江苏南京，210031
  • 出版日期:2022-11-15 发布日期:2022-11-15
  • 通讯作者: 刘义亭
  • 作者简介:张磊，男，1998年生，江苏扬州人，硕士研究生；研究方向为定位与自主导航技术。E-mail: 836228558@qq.com
  • 基金资助:
    国家自然科学基金青年基金（61903184）；江苏省自然科学基金青年基金（BK20181017，BK2019K186）；南京工程学院引进人才科研启动基金（YKJ2018822）；中国博士后科学基金第67批面上项目（2020M671292）；江苏省博士后科研资助计划（B类）（2019K186）；2021年度江苏省科技计划重点项目（产业前瞻与共性关键技术）（BE2021016—5）

Research on navigation and rectification of inspection robot based on ultrasonic sensor

Zhang Lei1, Liu Yiting1, 2*, Chen Guangming3, 4, Li Peijuan1   

  1. 1. Nanjing Institute of Engineering, Nanjing 211167, China;  2. Southeast University, Nanjing 210096, China;  3. Nanjing Agricultural University, Nanjing 210031, China;  4. Jiangsu Key Laboratory of Intelligent Agricultural Equipment, Nanjing 210031, China
  • Online:2022-11-15 Published:2022-11-15
  • Contact: Liu Yiting
  • About author:Zhang Lei

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摘要： 随着大数据及技术支撑型农业的兴起，越来越多的机器人开始在农业中得以应用。针对巡检机器人导航过程中位置精度误差和轨迹偏差较大的问题，研究一种基于超声波传感器的导航纠偏方法。通过对巡检机器人的位姿信息进行扩展卡尔曼滤波，将融合后的位姿用于其导航定位，将超声波传感器的量测数据结合融合后的位姿，根据巡检机器人与左右墙体之间的相对位置关系判断车体是否偏移，达到对导航轨迹纠偏的目的。试验表明，基于超声波传感器的导航纠偏在不发生转弯的情况下平均误差为0.011 3 rad，在发生一次转弯的情况下纠偏的平均误差为0.023 9 rad，可以降低巡检机器人与左右墙体发生碰撞的概率，提高导航过程中的工作性能。

关键词: 扩展卡尔曼滤波, 导航纠偏, 巡检机器人, 定位精度

Abstract: With the rise of big data and technological support, more and more robots have been applied in agriculture. In order to cope with the positioning error and trajectory deviation in the navigation process, a navigation correction method based on ultrasonic sensor was studied. By means of the extended Kalman filter of the position of the inspection robot, the fused position was used for its navigation and positioning, and the metrical data of the ultrasonic sensor was combined with the fused position. According to the relative position between the inspection robot and the walls, the deviation was judged to correct the navigation trajectory. The experiment showed that the average error of the navigation correction based on the ultrasonic sensor was 0.011 3 rad without turning, and the average error of the correction was 0.023 9 rad in the case of one turn. In this case, the chance that the inspection robot collided with the walls was lowered, and the working performance in the navigation process was enhanced.

Key words: extended Kalman filter, navigation correction, inspection robot, positioning accuracy

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