An analytical least-squares solution to the odometer-camera extrinsic calibration problem

Chao X. Guo, Faraz M. Mirzaei, Stergios Roumeliotis

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

21 Scopus citations

Abstract

In order to fuse camera and odometer measurements, we first need to estimate their relative transformation through the so-called odometer-camera extrinsic calibration. In this paper, we present a two-step analytical least-squares solution for the extrinsic odometer-camera calibration that (i) is not iterative and finds the least-squares optimal solution without any initialization, and (ii) does not require any special hardware or the presence of known landmarks in the scene. Specifically, in the first step, we estimate a subset of the 3D relative rotation parameters by analytically minimizing a least-squares cost function. We then back-substitute these estimates in the measurement constraints, and determine the rest of the 3D transformation parameters by analytically minimizing a second least-squares cost function. Simulation and experimental results are presented that validate the efficiency and accuracy of the proposed algorithm.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Robotics and Automation, ICRA 2012
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3962-3968
Number of pages7
ISBN (Print)9781467314039
DOIs
StatePublished - Jan 1 2012
Event 2012 IEEE International Conference on Robotics and Automation, ICRA 2012 - Saint Paul, MN, United States
Duration: May 14 2012May 18 2012

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Other

Other 2012 IEEE International Conference on Robotics and Automation, ICRA 2012
Country/TerritoryUnited States
CitySaint Paul, MN
Period5/14/125/18/12

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