Design and Realization of Localization Algorithm for Sweeping Robot Based on Monocular Ceiling Vision

WANG Xiao-tong; HUANG Lu

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Design and Realization of Localization Algorithm for Sweeping Robot Based on Monocular Ceiling Vision

更新时间：2026-09-04

- Design and Realization of Localization Algorithm for Sweeping Robot Based on Monocular Ceiling Vision
- Vol. 35, Issue 3, Pages: 125-129(2018)
- 作者机构：
  
  中国科学技术大学信息科学技术学院,安徽,合肥,230022
- 作者简介：
- 基金信息：
- DOI：
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- Published：2018
- 稿件说明：
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王晓彤, 黄鲁. 基于单目天花板视觉的扫地机器人定位算法设计及实现[J]. 微电子学与计算机, 2018, 35(3): 125-129, 134.

WANG Xiao-tong, HUANG Lu. Design and Realization of Localization Algorithm for Sweeping Robot Based on Monocular Ceiling Vision[J]. 2018, 35(3): 125-129.
王晓彤, 黄鲁. 基于单目天花板视觉的扫地机器人定位算法设计及实现[J]. 微电子学与计算机, 2018, 35(3): 125-129, 134. DOI：

WANG Xiao-tong, HUANG Lu. Design and Realization of Localization Algorithm for Sweeping Robot Based on Monocular Ceiling Vision[J]. 2018, 35(3): 125-129. DOI：

摘要

随着扫地机器人的逐渐普及

通过视觉传感器进行定位已成为亟待解决的关键问题.但由于嵌入式系统资源有限导致视觉定位实现技术难度大且效果差

因此采用单目相机顶视室内环境天花板的方法

能在减小计算量的同时解决单目尺度不定性的问题.首先

对采集的连续帧采用FAST结合Shi-Tomasi算法提取特征点

并使用ORB匹配算法进行匹配

结合视觉定位模型估计出全局定位位姿.然后

辅助使用价格低廉的传感器提供粗略数据

改进了ORB匹配算法.最后

设计了特征地图进行可视化实验验证

结果表明所提方案具有较好的定位精度与实时性.

Abstract

Vision Localization has become a crucial problem to be solved with the continuous popularity of sweeping robots. However

due to the limited resources of embedded systems

it is difficult to be realized and we can hardly get good performance. To address this challenge

in this paper the monocular camera which faces the ceiling is used to reduce the computational complexity and solve the uncertainty of monocular scale. Firstly

we extract and match the feature points of collected consecutive frames by using the FAST with Shi-Tomasi algorithm and ORB matching algorithm

and jointly consider the vision localization model to estimate the global positions. Then

the ORB matching algorithm is improved using the rough data provided by inexpensive sensors. Finally

we design a UI of feature map to perform visual experiments and the results show that our proposed scheme has high accuracy and low computational complexity.

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Keywords

references

Hess W, Kohler D, Rapp H, et al. Real-time loop closure in 2D LIDAR SLAM[C]//Robotics and Automation (ICRA), 2016 IEEE International Conference on. IEEE, 2016: 1271-1278.

Rublee E, Rabaud V, Konolige K, et al. ORB: An efficient alternative to SIFT or SURF[C]//Computer Vision (ICCV), 2011 IEEE International Conference on. IEEE, 2011: 2564-2571.

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Wang H, Mou W, Seet G, et al. Real-time visual odometry estimation based on principal direction detection on ceiling vision[J]. International Journal of Automation and Computing, 2013, 10(5): 397-404. DOI: 397

Wu C J, Tsai W H. Location estimation for indoor autonomous vehicle navigation by omni-directional vision using circular landmarks on ceilings[J]. Robotics and Autonomous Systems, 2009, 57(5): 546-555. DOI: 546

Birmingham, UK Laganiere R. OpenCV 2 computer vision application programming cookbook [M]. Birmingham, UK: Packt Publishing, 2011.

Sun Y D, Ding N, Qian H H, etal. Real-time monocular visual self-localization approach using natural circular landmarks for indoor navigation[C]//Proc of the IEEE International Conference on Robotics and Biomimetics. IEEE, 2012: 495-500.

Chen X H, Jia Y M. Indoor locallization for mobile robots using lampshade corners as landmarks: visual system calibration, feature extraction and experiments[J]. International Journal of Control, Automation, and Systems, 2014, 12(6): 1313-1322. DOI: 1313

ZHAO Chenchen, GONG Zhihui, LONG Yican, et al. The oblique stereo image matching with Shi-Tomasi features[J]. Journal of Geomatics Science and Technology, 2015, 32(1): 66-71. DOI: 66

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