Vision-based localization and mapping for an autonomous mower

Junho Yang, Soon-Jo Chung, Seth Andrew Hutchinson, David Johnson, Michio Kise

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

Abstract

This paper presents a vision-based localization and mapping algorithm for an autonomous mower. We divide the task for robotic mowing into two separate phases, a teaching phase and a mowing phase. During the teaching phase, the mower estimates the 3D positions of landmarks and defines a boundary in the lawn with an estimate of its own trajectory. During the mowing phase, the location of the mower is estimated using the landmark and boundary map acquired from the teaching phase. Of particular interest for our work is ensuring that the estimator for landmark mapping will not fail due to the nonlinearity of the system during the teaching phase. A nonlinear observer is designed with pseudo-measurements of each landmark's depth to prevent the map estimator from diverging. Simultaneously, the boundary is estimated with an EKF. Measurements taken from an omnidirectional camera, an IMU, and a ground speed sensor are used for the estimation. Numerical simulations and offline teaching phase experiments with our autonomous mower demonstrate the potential of our algorithm.

Original languageEnglish (US)
Title of host publicationIROS 2013
Subtitle of host publicationNew Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
Pages3655-3662
Number of pages8
DOIs
StatePublished - Dec 1 2013
Event2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013 - Tokyo, Japan
Duration: Nov 3 2013Nov 8 2013

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Other

Other2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013
CountryJapan
CityTokyo
Period11/3/1311/8/13

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Yang, J., Chung, S-J., Hutchinson, S. A., Johnson, D., & Kise, M. (2013). Vision-based localization and mapping for an autonomous mower. In IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 3655-3662). [6696878] (IEEE International Conference on Intelligent Robots and Systems). https://doi.org/10.1109/IROS.2013.6696878