Slippage detection and pose recovery for upward-looking camera-based SLAM using optical flow

Heewon Chae, Jae-Bok Song

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

4 Citations (Scopus)

Abstract

This paper deals with slippage detection and pose recovery during the SLAM process of mobile robot navigation. Mobile robots do not have a successful solution to recover when localization fails due to slippage. Unexpected inputs such as wheel slippage lead to false prediction during the SLAM process. In this paper, minimizing the risk of localization failure is proposed by applying optical flow to the ceiling image sequences as a slippage detector. The optical flow-based motion estimation results are applied to the prediction step of EKF-SLAM. Using optical flow, we can calculate a homogenous 2D affine transformation matrix. From this matrix we can calculate the relative pose between the two frames. The reliable motion estimation from the vision sensor enables slip detection during the prediction phase of EKF SLAM. The proposed method was successfully verified by several experiments with deliberate slippage in real environments.

Original languageEnglish
Title of host publicationInternational Conference on Control, Automation and Systems
Pages1108-1113
Number of pages6
DOIs
Publication statusPublished - 2013 Dec 1
Event2013 13th International Conference on Control, Automation and Systems, ICCAS 2013 - Gwangju, Korea, Republic of
Duration: 2013 Oct 202013 Oct 23

Other

Other2013 13th International Conference on Control, Automation and Systems, ICCAS 2013
CountryKorea, Republic of
CityGwangju
Period13/10/2013/10/23

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Keywords

  • ceiling
  • monocular SLAM
  • Optical flow
  • robust prediction
  • slippage
  • upward camera

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Chae, H., & Song, J-B. (2013). Slippage detection and pose recovery for upward-looking camera-based SLAM using optical flow. In International Conference on Control, Automation and Systems (pp. 1108-1113). [6704082] https://doi.org/10.1109/ICCAS.2013.6704082