INS/GPS integrated navigation for wheeled agricultural robot based on sigma-point kalman filter

Yuliang Zhang, Feng Gao, Lei Tian

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

Abstract

This paper describes a numerical robust and computational efficient square-root central difference Kalman filter (SRCDKF) and put it into the application of state estimation of Inertial Navigation System (INS)/GPS integrated navigation for wheeled agricultural robot to overcome the flaws exist in EKF (Extended Kalman Filter). A standard INS mechanization with quaternion form attitude expression is introduced and a GPS antenna position compensated observation model is used. Based on the model above, both EKF and SRCDKF are implemented, and their performances are compared through simulation under several situations. Results indicate that the SRCDKF is much more robust and superior than EKF in the existence of large initial heading errors, short period of GPS outrage and low-cost IMU (Inertial Measurement Unit). It based a good foundation for the accurate and robust control of the agricultural robot.

Original languageEnglish (US)
Title of host publication2008 Asia Simulation Conference - 7th International Conference on System Simulation and Scientific Computing, ICSC 2008
Pages1425-1431
Number of pages7
DOIs
StatePublished - 2008
Event2008 Asia Simulation Conference - 7th International Conference on System Simulation and Scientific Computing, ICSC 2008 - Beijing, China
Duration: Oct 10 2008Oct 12 2008

Publication series

Name2008 Asia Simulation Conference - 7th International Conference on System Simulation and Scientific Computing, ICSC 2008

Other

Other2008 Asia Simulation Conference - 7th International Conference on System Simulation and Scientific Computing, ICSC 2008
Country/TerritoryChina
CityBeijing
Period10/10/0810/12/08

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software

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