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Attitude determination by integration of MEMS inertial sensors and GPS for autonomous agriculture applications

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Abstract

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) technologies, which has widespread usage in industry, is also regarded as an ideal solution for automated agriculture because it fulfils the accuracy, reliability and availability requirements of industrial and agricultural applications. Agriculture applications use position, velocity and heading information for automated vehicle guidance and control to enhance the yield and quality of the crop, and in order to vary the application of fertilizer and herbicides according to soil heterogeneity at sub-field level. A loosely coupled GPS/INS integration algorithm known as “AhrsKf” is introduced for automated agriculture vehicle guidance and control utilizing MEMS inertial sensors and GPS. The AhrsKf can produce high-frequency attitude solutions for the vehicle’s guidance and control system, by using inputs from a single survey grade L1/L2 antenna, eliminating the need for the previous two antenna solutions. Given its agricultural application, the AhrsKf has been implemented with some specific design features to improve the accuracy of the attitude solution including, temperature compensation of the inertial sensors, and the aid of plough lines of farm lands. To evaluate the AhrsKf solution, two benchmarking tests have been conducted by using a three-antenna GPS system and NovAtel’s SPAN-CPT. The results have demonstrated that the AhrsKf solution is stable and can correctly track the movement of the farming vehicle.

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Acknowledgments

This work was funded by the Australian Research Council Linkage project LP0667730. Leica Geosystems is the industrial partner. The authors acknowledge GPSat Systems Ltd for providing the SPAN-CPT used in the test. Damien Dusha and William Kellar from Leica Geosystems are acknowledged for their collaboration in the research.

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Authors and Affiliations

  1. School of Surveying & Spatial Information Systems, University of New South Wales, Sydney, 2052, Australia

    Yong Li, Mahmoud Efatmaneshnik & Andrew G. Dempster

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  1. Yong Li
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  2. Mahmoud Efatmaneshnik
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  3. Andrew G. Dempster
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Correspondence to Yong Li.

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Li, Y., Efatmaneshnik, M. & Dempster, A.G. Attitude determination by integration of MEMS inertial sensors and GPS for autonomous agriculture applications. GPS Solut 16, 41–52 (2012). https://doi.org/10.1007/s10291-011-0207-y

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  • DOI: https://doi.org/10.1007/s10291-011-0207-y

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