A low-cost integrated positioning system for autonomous off-highway vehicles

Abstract

This article reports a method for integrating a low-cost positioning system, constructed using a Garmin N17 global positioning system (GPS) and an integrated inertial sensor unit, consisting of three single-axis microelectromechanical system (MEMS) gyros and one triaxial MEMS accelerometer, for autonomous off-highway vehicle use. Based on a vehicle position—velocity—attitude (PVA) model, a data fusion algorithm was formulated to extract more accurate and reliable positioning information from the raw data sensed by the GPS and inertial sensor unit. The developed integrated positioning system (IPS) was evaluated on an agricultural utility vehicle on three different sites. A real-time kinematic (RTK) differential GPS unit, capable of providing 2–3cm dynamic positioning accuracy while the position dilution of precision is low enough, was installed on the test vehicle to provide accurate positioning references in those evaluation tests. Results obtained from those tests showed that, when the vehicle was travelling on paved roads near buildings and/or under the trees, the maximum positioning error of the developed IPS was 0.50m, and that this maximum error level was reduced to 0.30m when the vehicle was travelling in open fields. The IPS could provide a position update rate at 50Hz; even the GPS could provide only a 1Hz update rate. Test results also revealed that this system could continuously provide accurate position signals when the GPS signal is lost for up to 30s. This research verified that a low-cost IPS could provide satisfactory position information for autonomous off-highway vehicle uses.

Keywords

global positioning system inertial sensors sensor fusion Kalman filter off-highway vehicle

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References

Huang

Tan

H.-S.

A low-order DGPS-based vehicle positioning system under urban environment. IEEE/ASME Trans. Mechatronics, 2006, 11, 567–575.

Schonberg

Ojala

Suomela

Torpo

Halme

Positioning an autonomous off-road vehicle by using fused DGPS and inertial navigation. In Proceedings of the Second IFAC Conference on Intelligent autonomous vehicles, Espoo, Finland, 1995 pp. 211–216 (Finnish Society of Automation, Helsinki).

Taylor

Brunsdon

Olden

Steup

Winter

GPS accuracy estimation using map matching techniques: Applied to vehicle positioning and odometer calibration. Computers, Environment Urban Systems, 2006, 30, 757–772.

O'Connor

Bell

Elkaim

Parkinson

Automatic steering of farm vehicles using GPS. In Proceedings of the Third International Conference on Precision agriculture, Minneapolis, Minnesota, USA, 1996 pp. 767–778 (American Society of Agronomy-Crop Science Society of America-Soil Science Society of America, Madison, Wisconsin, USA).

Bell

Automatic tractor guidance using carrier- phase differential GPS. Computers Electronics Ag- ric., 2000, 25, 53–66.

Stafford

J. V.

Ambler

In-field location using GPS for spatially variable field operations. Computers Electronics Agric., 1994, 11, 23–36.

Farrell

J. A.

Givargis

T. D.

Barth

M. J.

Real-time differential carrier phase GPS-aided INS. IEEE Trans. Control Systems Technol., 2000, 8, 709–721.

Dissanayake

Sukkarieh

Nebot

Durrant-Whyte

The aiding of low-cost strapdown inertial measurement unit using vehicle model constraints for land vehicle applications. IEEE Trans. Robotics Automn, 2001, 17, 731–747.

Kacemi

Reboul

Benjelloun

Information fusion in a hybrid tightly coupled GPS/ dead-reckoning positioning system. In Proceedings of the IEEE International Conference on Multisensor fusion and integration for intelligent systems, Heidelberg, Germany, 2006 pp. 450–455 (IEEE, New York).

10.

Uenoyama

Nakamura

Nishitani

Novel position estimation for GPS and low-cost INS fusion. In Proceedings of the 2006 IEEE/ION Position, Location, and Navigation Symposium, San Diego, California, USA, 2006 pp. 630–635 (IEEE, New York).

11.

Brown

R. G.

Hwang

P. Y. C.

Introduction to random signals and applied Kalman filtering, 3rd edition, 1997 (John Wiley, New York).

12.

Grewal

M. S.

Andrews

A. P.

Kalman filter: theory and practice using MATLAB, 2nd edition, 2001 (John Wiley, New York).

13.

Farrell

J. A.

Barth

The global positioning system and inertial navigation, 1999 (McGraw-Hill, New York).

14.

Guo

Development of a low-cost navigation system for autonomous off-road vehicles. PhD Dissertation, Department of Agricultural Engineering, University of Illinois at Urbana-Champaign, Illinois, USA, 2003.

15.

Han

Zhang

Noh

Kalman filter of DGPS positions for a parallel tracking application. Trans. ASA, 2002, 45, 553–559.