scholarly journals Design and recognition of artificial landmarks for reliable indoor self-localization of mobile robots

2017 ◽  
Vol 14 (1) ◽  
pp. 172988141769348 ◽  
Author(s):  
Xu Zhong ◽  
Yu Zhou ◽  
Hanyu Liu

This article presents a self-localization scheme for indoor mobile robot navigation based on reliable design and recognition of artificial visual landmarks. Each landmark is patterned with a set of concentric circular rings in black and white, which reliably encodes the landmark’s identity under environmental illumination. A mobile robot in navigation uses an onboard camera to capture landmarks in the environment. The landmarks in an image are detected and identified using a bilayer recognition algorithm: A global recognition process initially extracts candidate landmark regions across the whole image and tries to identify enough landmarks; if necessary, a local recognition process locally enhances those unidentified regions of interest influenced by illumination and incompleteness and reidentifies them. The recognized landmarks are used to estimate the position and orientation of the onboard camera in the environment, based on the geometric relationship between the image and environmental frames. The experiments carried out in a real indoor environment show high robustness of the proposed landmark design and recognition scheme to the illumination condition, which leads to reliable and accurate mobile robot localization.

Author(s):  
Hanyu Liu ◽  
Xu Zhong ◽  
Yu Zhou

In this paper, we present an omnidirectional artificial landmark model and a robust artificial landmark recognition algorithm for indoor mobile robot positioning. The landmark model encodes identities with nested circles in black and white, which provides stable edge response and enables strong tolerance to various lighting conditions and perspective distortions. The corresponding positioning system uses a single upward-facing webcam as the vision sensor to capture landmarks. To address the effect of the lighting and sensing noise, the topological contour analysis is applied to detect landmarks, and the dynamic illumination adjustment is used to assist landmark recognition. Based on the landmark recognition, the absolute position of the camera in the environment is estimated using a trilateration algorithm. The landmark model and positioning system are tested with a mobile robot in a real indoor environment. The results show that the purposed technique provides autonomous indoor positioning for mobile robots with high robustness and consistency.


2013 ◽  
Vol 365-366 ◽  
pp. 967-970 ◽  
Author(s):  
Vladimir Popov ◽  
Anna Gorbenko

Visual landmarks are extensively used in contemporary robotics. There are a large number of different systems of visual landmarks. In particular, fingerprints give us unique identifiers for visually distinct locations by recovering statistically significant features. Therefore, fingerprints can be used as visual landmarks for mobile robot navigation. To create fingerprints we need one-dimensional color panoramas of high quality. In this paper, we consider a method for building the panoramic image using string matching algorithms. In particular, we propose the shortest common ordered supersequence problem.


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