A novel drift compensating method for orientation measurement system in VR applications

Changyu He*, Xiaoming Hu, Yue Liu, Yongtian Wang, Haobo Cheng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Accurate and fast estimation of a target's orientation with inertial/magnetic sensors is widely applied in many Virtual Reality applications. Due to the abrupt movement of targets, the accuracy of the motion estimate degrades. In this paper, we propose a quaternion-based Kalman filter for a multi-sensor system which utilizes a low-cost tri-axis accelerometer, a tri-axis gyroscope and a tri-axis magnetometer. The proposed Kalman filter combines a novel error model in its measurement update equation which makes it possible to separate the acceleration error from the gravitational acceleration, and achieve an accurate orientation estimate. Due to the computational efficiency of the proposed algorithm, the system is suitable for human motion tracking applications in real-time. Results of simulations and experiments prove the efficiency of the proposed algorithm.

Original languageEnglish
Title of host publication2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings
Pages2482-2487
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2012 - Graz, Austria
Duration: 13 May 201216 May 2012

Publication series

Name2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings

Conference

Conference2012 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2012
Country/TerritoryAustria
CityGraz
Period13/05/1216/05/12

Keywords

  • Acceleration Error
  • Inertial/Magnetic Sensors
  • Kalman Filter
  • Motion Estimation
  • Quaternion

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