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An Integrated Planning of Exploration, Coverage, and Object Localization for an Efficient Indoor Semantic Mapping

  • Diar Fahruddin Sasongko
  • Jun Miura
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 867)

Abstract

This paper describes an integrated viewpoint planner for indoor semantic mapping. Mapping of an unknown environment can be viewed as an integration of various activities: exploration, (2D or 3D) geometrical mapping, and object detection and localization. An efficient mapping entails selecting good viewpoints. Since a good viewpoint for one activity and that for another could be shared or conflicting, it is desirable to deal with all such activities at once, in an integrated manner. We use a frontier-based exploration, an area coverage approach for geometrical mapping, and object recognition model-based verification for generative respective viewpoints, and get the best next viewpoint by solving a travelling salesman problem. We carry out experiments using a realistic 3D robotic simulator to show the effectiveness of the proposed integrated viewpoint planning method.

Keywords

Viewpoint planning Semantic mapping Mobile robot 

Notes

Acknowledgment

This work is in part supported by JSPS KAKENHI Grant Number 17H01799 and the Hibi Science Foundation.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringToyohashi University of TechnologyToyohashiJapan

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