A new approach to map joining for depth-augmented visual SLAM

Chien Hung Liu, Kai-Tai Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper, a novel scheme is proposed to improve real-time performance of simultaneous localization and mapping (SLAM) of a mobile robot based on depth-augmented visual features. In this design, the robot has two stages in navigation applications, namely the map building stage and the map usage stage. In the map-building stage, a local map is built to join into the global map. For the map-usage stage, instead of using the global map, the local maps facilitate real-time path tracking control of the robot. Using of local maps has the merit of reducing the computational complexity of EKF-SLAM. In the map joining procedure, deviations of adjacent local maps are corrected based on local features. Loop closure detection is used to determine whether the local map building is completed. A Kinect sensor is adopted to realize the proposed method. Navigation experiments on a wheeled mobile robot show that the motion error of robot localization is within 0.1m for a travel over 83m.

Original languageEnglish
Title of host publication2013 9th Asian Control Conference, ASCC 2013
DOIs
StatePublished - 31 Oct 2013
Event2013 9th Asian Control Conference, ASCC 2013 - Istanbul, Turkey
Duration: 23 Jun 201326 Jun 2013

Publication series

Name2013 9th Asian Control Conference, ASCC 2013

Conference

Conference2013 9th Asian Control Conference, ASCC 2013
CountryTurkey
CityIstanbul
Period23/06/1326/06/13

Keywords

  • mobile robot navigation
  • SLAM
  • Visual features

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  • Cite this

    Liu, C. H., & Song, K-T. (2013). A new approach to map joining for depth-augmented visual SLAM. In 2013 9th Asian Control Conference, ASCC 2013 [6606243] (2013 9th Asian Control Conference, ASCC 2013). https://doi.org/10.1109/ASCC.2013.6606243