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Carnegie Mellon Robotics Institute

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Abstract

This paper presents three localization algorithms using radio beacons that provide the ability to measure range only. Obtaining range from radio has the advantage that line of sight between the beacons and the transponder is not required, and the data association problem can be completely avoided. An extended Kalman filter, a particle filter, and a nonlinear sliding batch method are used to fuse range data with dead reckoning data collected from a real system, and results are demonstrated. The extended Kalman filter is also applied to the SLAM problem.

Notes

Number of pages: 60

Text Reference

Derek Kurth, "Range-Only Robot Localization and SLAM with Radio," master's thesis, tech. report CMU-RI-TR-04-29, Robotics Institute, Carnegie Mellon University, May, 2004

BibTeX Reference

@mastersthesis{Kurth_2004_4741,
   author = "Derek Kurth",
   title = "Range-Only Robot Localization and SLAM with Radio",
   school = "Robotics Institute, Carnegie Mellon University",
   month = "May",
   year = "2004",
   number= "CMU-RI-TR-04-29",
   address= "Pittsburgh, PA",
}

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