Compression of topological models and localization using the global appearance of visual information

Luis Paya Castello, Walterio Mayol-Cuevas, Sergio Cebollada, O Reinoso

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

4 Citations (Scopus)
278 Downloads (Pure)

Abstract

In this work, a clustering approach to obtain compact topological models of an environment is developed and evaluated. The usefulness of these models is tested by studying their utility to solve the robot localization problem subsequently. Omnidirectional visual information and global appearance descriptors are used both to create and compress the models and to estimate the position of the robot. Comparing to the methods based on the extraction and description of landmarks, global appearance approaches permit building models that can be handled and interpreted more intuitively and using relatively straightforward algorithms to estimate the position of the robot. The proposed algorithms are tested with a set of panoramic images captured with a catadioptric vision sensor in a large environment under real working conditions. The results show that it is possible to compress substantially the visual information contained in topological models to arrive to a balance between the computational cost and the accuracy of the localization process.

Original languageEnglish
Title of host publicationICRA 2017 - IEEE International Conference on Robotics and Automation
Place of Publication9781509046348
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages5630-5637
Number of pages8
ISBN (Electronic)9781509046331
DOIs
Publication statusPublished - 24 Jul 2017
Event2017 IEEE International Conference on Robotics and Automation, ICRA 2017 - Singapore, Singapore
Duration: 29 May 20173 Jun 2017

Conference

Conference2017 IEEE International Conference on Robotics and Automation, ICRA 2017
CountrySingapore
CitySingapore
Period29/05/173/06/17

Keywords

  • Visualization
  • Clustering algorithms
  • Computational modeling
  • Robots
  • image coding
  • Histograms
  • Sparse matrices

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