This paper compares the use of an inertial navigation system INS and a multiple GPS antenna system for attitude determination of an off-road vehicle. The INS system currently provides a less expensive attitude solution than the multiple GPS antenna system. Additionally, the INS system does not suffer from GPS errors resulting from multipath and antenna blockages. A Kalman filter incorporates the INS measurements with ( ) centimeter-level carrier-phase differential GPS DGPS measurements from one position antenna for complete position and attitude estimation of an off-road vehicle. The centimeter-level accuracy of DGPS allows for precise calibrations of the INS system for accurate attitude estimation. The paper shows that a low-cost INS system is capable of providing the attitude accuracy necessary for centimeter-level control of an off-road vehicle. Results of using the INS system in conjunction with DGPS position measurements to autonomously control a farm tractor are presented.

High-precision ‘autofarming’ makes possible farming techniques previously impractical using metre-level Differential GPS-based control systems: techniques such as tape irrigation, the elimination of guess rows, and precise contour farming. A Carrier-Phase Differential gps positioning and attitude system with centimetre-level and 0·1° accuracy was installed in a large farm tractor. Four types of trajectories (lines, arcs, spirals, and curves) were identified as basic building blocks necessary to generate a ‘global’ trajectory for a realistic autofarming path. Information about each trajectory type was translated into reference state specifications that a linear controller used to control the tractor over velocities between 0·7 and 2·8 m/s to within approximately 6 cm (1 σ) without implement and 10 cm (1 σ) with implement on sloped terrain using a previously developed tractor model. These results are a significant step towards a realistic autofarming system because they not only demonstrate accurate control over various realistic operating speeds but over different types of trajectories necessary for a commercial system.

Accurately modeling the relationship between the yaw rate and the steer angle of an off road vehicle is important when developing control laws for autonomous vehicle guidance. This relationship is a function of various factors such as vehicle configuration, loading, and ground conditions. A simple model was developed that accounted for time varying dependencies and a leastsquares filter based on the LMS algorithm was created to identify this non-linear dependence in real time. An autonomously guided farm tractor fitted with GPS based attitude measurement that is used for control system research served as the test platform. Excellent agreement between predicted steering effectiveness and measured steering effectiveness.

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