IMU-RGBD camera 3D pose estimation and extrinsic calibration: Observability analysis and consistency improvement

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

28 Scopus citations

Abstract

In this paper, we address the problem of extrinsically calibrating an inertial measurement unit (IMU) with respect to an RGBD sensor. In particular, we study the observability of the nonlinear IMU-RGBD calibration system and prove that the calibration parameters are observable given observations to a single point feature. Moreover, we show that the system has four unobservable directions corresponding to the global translation and rotations about the gravity vector. Based on the results of the observability analysis, we design a consistency-improved, observability constrained (OC) extended Kalman filter (EKF)-based estimator for calibrating the sensor pair while at the same time tracking its pose and creating a 3D map of the environment. Finally, we validate the key findings of the observability analysis and assess the performance of the OC-EKF estimator both in simulation and experimentally.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Robotics and Automation, ICRA 2013
Pages2935-2942
Number of pages8
DOIs
StatePublished - Nov 14 2013
Event2013 IEEE International Conference on Robotics and Automation, ICRA 2013 - Karlsruhe, Germany
Duration: May 6 2013May 10 2013

Publication series

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

Other

Other2013 IEEE International Conference on Robotics and Automation, ICRA 2013
CountryGermany
CityKarlsruhe
Period5/6/135/10/13

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