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Carnegie Mellon Robotics Institute

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Abstract

This paper presents a perception-based GPS-free approach for localizing a mobile robot in an orchard environment. An extended Kalman ﬁlter (EKF) algorithm is presented that uses a wheel odometry prediction step and laser rangeﬁnder update steps. There are two update steps, one that uses measurements to reﬂective point features and one that uses measurements to linear features formed by tree rows. The features are associated to landmarks in previously surveyed maps. The practical issues of dealing with uncertainty both from the environment and the on-board sensors are discussed and accounted for. The resulting algorithm is demonstrated in over 20km of online operation in a variety of real orchard environments.

Notes

Associated Center(s) / Consortia: Field Robotics Center

Associated Project(s): Comprehensive Automation for Specialty Crops

Number of pages: 6

Note: Nominee, Best Automation Paper

Text Reference

Jacqueline Libby and George A. Kantor, "Deployment of a Point and Line Feature Localization System for an Outdoor Agriculture Vehicle ," 2011 IEEE International Conference on Robotics & Automation (ICRA 2011), May, 2011.

BibTeX Reference

@inproceedings{Libby_2011_6802,
   author = "Jacqueline Libby and George A Kantor",
   title = "Deployment of a Point and Line Feature Localization System for an Outdoor Agriculture Vehicle ",
   booktitle = "2011 IEEE International Conference on Robotics & Automation (ICRA 2011)",
   month = "May",
   year = "2011",
   Notes = "Nominee, Best Automation Paper"
}

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