An Indoor Positioning Method of Monocular Vision Robot Based on Floor Features

Jie Yun-fei; Everett Wang; Zhong You-dong; Zhi Kai-xuan; Xiong Chao-wei

doi:10.12052/gdutxb.190143

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An Indoor Positioning Method of Monocular Vision Robot Based on Floor Features

更新时间：2026-05-27

- An Indoor Positioning Method of Monocular Vision Robot Based on Floor Features
- Vol. 37, Issue 5, Pages: 31-37(2020)
- 作者机构：
  
  广东工业大学信息工程学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.190143
  CLC： TP242
- Online First：17 September 2020，
  
  Published：2020
- 稿件说明：
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揭云飞, 王峰, 钟有东, 智凯旋, 熊超伟. 基于地面特征的单目视觉机器人室内定位方法[J]. 广东工业大学学报, 2020, 37(5): 31-37.

Jie Yun-fei, Everett Wang, Zhong You-dong, et al. An Indoor Positioning Method of Monocular Vision Robot Based on Floor Features[J]. 2020, 37(5): 31-37.
揭云飞, 王峰, 钟有东, 智凯旋, 熊超伟. 基于地面特征的单目视觉机器人室内定位方法[J]. 广东工业大学学报, 2020, 37(5): 31-37. DOI： 10.12052/gdutxb.190143.

Jie Yun-fei, Everett Wang, Zhong You-dong, et al. An Indoor Positioning Method of Monocular Vision Robot Based on Floor Features[J]. 2020, 37(5): 31-37. DOI： 10.12052/gdutxb.190143.

摘要

针对高精度的机器人室内定位方法中成本过高的问题

提出一种基于地面特征的单目视觉机器人室内定位方法。该方法通过安装在机器人底盘的单目鱼眼摄像头采集地面图片

并经过一系列图像处理

将得到的地面方格直线和相机的位姿关系作为观测量

通过推导出观测方程并根据扩展卡尔曼滤波算法得到机器人的位置信息。基于机器人当前时刻位置数据和地面的固定方格大小提出线预测算法

有效地排除干扰线段的影响。实验结果表明

该机器人室内定位方法定位精度可以达到2 cm

具有较好的鲁棒性

能够为低成本的机器人室内定位提供较好的技术参考。

Abstract

In order to solve the problem of high cost in high-precision robot indoor positioning method

an indoor positioning method based on ground features for monocular vision robot is proposed. This method collects the ground image through the monocular fisheye camera installed on the robot chassis

and after a series of image processing

the relationship between the ground grid straight line and the pose of the camera is used as the observational measurements

then the position information of the robot is obtained by deriving the observation equation and the extended Kalman filter algorithm. Based on the current time position data of the robot and the fixed square size of the ground

a line prediction algorithm is proposed to effectively eliminate the influence of the interference line segment. The experimental results show that the positioning accuracy of the robot indoor positioning method can reach 2 cm

which has good robustness and also can provide a good technical reference for low-cost robot indoor positioning.

关键词

Keywords

references

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