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Reduction of the uncertainty in feature tracking

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Abstract

It is difficult to establish feature correspondences between distant viewpoints for panoramic images. For reliable navigation and development a human-like capability of interaction with the surrounding environment, we need a method of reduction of the uncertainty in feature tracking. To obtain a method of reduction of the uncertainty in feature tracking, we propose to use an algorithm for the problem of the longest common subsequence for a set of circular strings. We consider an explicit reduction from the problem of the longest common subsequence for a set of circular strings to the satisfiability problem. This reduction allows to obtain an efficient algorithm for finding the longest common subsequence for a set of circular strings. We present a general scheme of the method of reduction of the uncertainty in feature tracking. We considered the visual homing task to demonstrate the capabilities of our approach to solve the problem of reduction of the uncertainty in feature tracking. We present experimental results for the method of reduction of the uncertainty in feature tracking and novel robot visual homing methods.

Keywords

Visual navigation Feature tracking Mobile robots Longest common subsequence Satisfiability problem 

Notes

Acknowledgements

The research of Anna Gorbenko was partially supported by the Ministry of Education and Science of the Russian Federation project “Combinatorial models in computer science and their applications”.

Compliance with Ethical Standards

Conflict of interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

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Authors and Affiliations

  1. 1.Department of Intelligent Systems and Robotics of the Regional Educational and Scientific Center of Intelligent Systems and Information Security, Institute of Natural Sciences and MathematicsUral Federal UniversityEkaterinburgRussian Federation

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