It is difficult to design controllers for the complicated dynamics of omnidirectional vehicles steered by multiple wheels with distributed traction force. In this paper, the dynamic model of a three-wheel omnidirectional vehicle, which is linearized to simplify controller design, is developed. The conditions of making its dynamics linear are derived first. Then, a strategy of planning wheel velocities to satisfy these conditions is proposed. Consequently, three-wheel omnidirectional vehicle can be easily treated by classical linear control theories. Finally, a linear optimal tracker is designed to control the omnidirectional vehicle for desired movement trajectories. In particular, the dynamic model includes the motors installed in the three-wheel omnidirectional vehicle, making it a practical model. Three kinds of vehicle trajectories illustrate the planning of wheel trajectories for linearizing the vehicle dynamics, and simulations demonstrate the performance of the linear optimal tracker. In addition, experimental results of a practical three-wheel omnidirectional vehicle are also included.

In future real-time systems such as those required for intelligent autonomous vehicle control, we need flexibility in choosing the set of services to support under varying environmental conditions and system states. It is not feasible to make an optimal choice of services at run-time, so we propose a method of ranking the services pre-run-time, based on the ‘utility' of each service. This paper focuses on the problem of calculating a ‘value' for the utility of each service alternative. We show how to derive values systematically and rationally, using Measurement Theory and Decision Analysis. The approach relies on engineering judgement and data input by a domain expert. In the context of autonomous vehicles, we believe that such knowledge would be available, making ‘value-based scheduling' a feasible approach.

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.