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Vision-Based Localization and Mapping for an Autonomous Mower

Yang, Junho and Chung, Soon-Jo and Hutchinson, Seth and Johnson, David and Kise, Michio (2013) Vision-Based Localization and Mapping for an Autonomous Mower. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE International Conference on Intelligent Robots and Systems. IEEE , Piscataway, NJ, pp. 3655-3662. ISBN 978-1-4673-6358-7. http://resolver.caltech.edu/CaltechAUTHORS:20161221-141750231

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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.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1109/IROS.2013.6696878DOIArticle
http://ieeexplore.ieee.org/document/6696878/?arnumber=6696878PublisherArticle
ORCID:
AuthorORCID
Chung, Soon-Jo0000-0002-6657-3907
Hutchinson, Seth0000-0002-3949-6061
Additional Information:© 2013 IEEE. Date Added to IEEE Xplore: 06 January 2014. This material is based on work supported by John Deere. The authors acknowledge Dr. Ashwin Dani for useful discussions on designing the observer. The authors also thank Colin Das for his help on the experiments.
Group:GALCIT
Funders:
Funding AgencyGrant Number
John DeereUNSPECIFIED
Record Number:CaltechAUTHORS:20161221-141750231
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20161221-141750231
Official Citation:J. Yang, S. J. Chung, S. Hutchinson, D. Johnson and M. Kise, "Vision-based localization and mapping for an autonomous mower," 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, 2013, pp. 3655-3662. doi: 10.1109/IROS.2013.6696878
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:73100
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:21 Dec 2016 22:48
Last Modified:18 May 2017 21:29

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