This chapter discusses the issue of machine perception from the perspective of a system design process. The three issues of information gathering, data representation and reasoning are discussed, leading to a general high-level model of the problem. The model is intended to be generic enough to allow a wide variety of tasks to be performed using a single set of sensory data. It is argued that the model has a direct correspondence with some recent biological models. Finally, an application is presented showing how the model may be applied to solving real-world problems, specifically an autonomous system operating in outdoor unstructured environments.

This paper presents a data-fusion and interpretation system for operation of an Autonomous Ground Vehicle (AGV) in outdoor environments. It is a practical implementation of a new model for machine perception and reasoning, which has its true utility in its applicability to increasingly unstructured environments. This model provides a cohesive, sensor-centric and probabilistic summary of the available sensory data and uses this richly descriptive data to enable robust interpretation of a scene. A general model is described and the development of a specific instance of it is described in detail. Preliminary results demonstrate the utility of the approach in very large, unstructured, outdoor environments.

It has been estimated that there are 250 million indigenous peoples living in more than 70 countries. Indigenous peoples have a particular relationship with the land and their natural environment, which can be viewed as part of their cultural patrimony as well as their means of economic support. The land provided them with both physical and spiritual sustenance. The relationship that indigenous peoples have with the land has been under threat since the development of the European Empires from the 16 Century. The latter brought the colonisation of the indigenous peoples’ lands and the commercial exploitation of the natural resources these contain. These processes have continued in the successor States that have replaced the European Empires. The consequences for the indigenous peoples have often been their marginalisation in society and their social exclusion.

This paper presents the modelling of an autonomous amphibious vehicle developed at the Australian Centre for Field Robotics, Sydney. All parts of the vehicle’s driveline from the engine, CVT, gearbox to wheels are analysed and modelled. Results from simulation, compared with data from characterising experiments, show that these models are valid and can be used for the control purpose. Keyword: automotive, CVT, diffenrential, skidsteering List of symbols: Ne: Engine speed Nc: CVT output speed NG: Gearbox output speed Nd: Speed of differential case (=NG) NdR: Differential’s output speed on right side NdL: Differential’s output speed on left side NwR: Right wheel speed NwL: Left wheel speed Te: Engine torque Tfric,e: Engine friction torque Tec: Load on engine Tc: Load on CVT Tfric,G: Gearbox friction torque TG: Load on gearbox Tfric,D: Differential friction torque Td: Load on differential’s case TdR: Load on differential’s right output TdL: Load on diffrential’s left output TwR: Load from right wheels TwL: Load from left wheels Tfric,w: Wheel friction torque K1: CVT gear ratio K2: Gearbox gear ratio K3: Chain system gear ratio r: Wheel radius

This paper presents a method for the fusion of millimetre wave radar and nightvision sensors to generate an information-rich representation of the environment. The data from each of the sensors is divided into unstructured spatial objects according to the data available to that sensor. A hyperdimensional representation then constructed from these objects, with the observable characteristics providing the axes. This representation can then be provided to target extraction, classification and tracking algorithms to achieve advanced machine sensing and perception tasks. This differs significantly from the traditional approaches to this problem in which target identification is completed for each individual sensor and these estimates are then combined. The results of initial field trials are used to demonstrate the feasibility of this approach.

This paper presents a method for the fusion of mm-Wave Radar and Nightvision data. This method differs from traditional approaches in that the information is combined before any judgement is made regarding the number, type or location of any objects within the sensor field. The characteristic information is combined and is shown to yield an environmental representation containing both sensor signatures for each object, significantly simplifying and improving the performance of detection, classification and tracking algorithms. Results of field trials are used to demonstrate the method’s effectiveness.

Model equations of state for solid and liquid iron in the range of conditions of interest to geophysicists are developed with the constraints provided by available experimental data and theoretical calculations. Sensitivities to various uncertainties are indicated by example. The important role of the two‐phase liquid‐solid region in the properties of the inner and outer core is illustrated.

Theoretical calculations, together with diamond anvil measurements on the iron γ‐ε phase boundary to high pressure, suggest that a new bcc phase appears in iron at high pressures and temperatures. This bcc phase may be responsible for the shock anomaly observed in iron at 2.0 Mbar, and the solid inner core of the Earth may be in this phase.

We follow Rosenfeld in comparing fluid-phase thermal conductivities for several simple pair potentials. Within about ten percent these (nonelectronic) conductivities satisfy a corresponding states relation involving the equilibrium entropy. This corresponding states relation, deduced directly from the results of computer simulations, is also suggested by hard-sphere perturbation theory and by the quasiharmonic cell-model approach. The conductivity-entropy relation should be useful for estimating transport coefficients from the equation of state of monatomic fluids with arbitrary pair potentials.

A semiempirical equation of state for iron has been constructed by dividing the total energy into mean field, interatomic pair potential, and electronic thermal terms. The five adjustable parameters are fitted to the experimental isotherm, Hugoniot, and melting curve. Superimposing the estimated pressure and temperature conditions of the presumably pure solid iron inner core of the earth onto the calculated phase diagram shows an unexpected discrepancy.

Recent dynamic compression data for carbon are discussed which suggests that metallic carbon has unexpected thermodynamics properties, both in having a lower density and energy of formation and a higher melting temperature. On the basis of these properties the diamond phase of carbon is now predicted to transform to a solid phase of metallic carbon at all pressures above the graphite triple point.

Temperature data from optical intensity measurements through anvils at high shock pressures are reported for magnesium samples. When account is taken for imperfect gaps at the anvil interface, the temperature measurements are shown to determine the melting line of magnesium at pressures from 40 to 50 GPa (400 to 500 kbar). The resulting high-pressure melting line for magnesium is in good agreement with the Lindemann law, with reasonable high pressure values for the Grüneisen coefficient γG.

Thermal conduction processes at material interfaces representative of those produced by shock compression are studied in order to understand the temperature history at the interface. The transient effects due to small gaps and thin layers are calculated, as well as the modifications due to a melting transition in one of the materials.

In shock-wave compression experiments in which the interface temperature between two different materials is important, it is necessary to take account of more than the usual ideal shock impedance matching conditions. Several examples are discussed by means of hydrodynamic analysis of the interaction of strong shock waves with nonideal interfaces. It is demonstrated that significant residual thermal inhomogeneities exist near the interface which may be of use in understanding and measuring thermal properties of shock-compressed materials.

High pressure shock wave data on a wide variety of metals indicates that electronic transitions are continuously distributed in the liquid phase and accompanied by melting maxima. A qualitative explanation for this behavior is suggested.

Isothermal compression data derived from shock-wave and static-compression measurements on metals exhibit a nearly precise linear relation between the logarithm of the bulk modulus and the specific volume up to volume changes of 40%. As a result, solid isotherms can be accurately fitted or extrapolated in this range by means of two parameter functions of either a Birch or a modified Tait form.

Most of the softer metals exhibit a low-temperature close-packed phase, an intermediate-temperature body-centered phase, and a high-temperature fluid phase. Here we relate this behavior to that of theoretical model systems in which particles interact with the inverse power potential φ (r)=ε ( σ / r)n. We show that the same three-phase behavior occurs for the models provided that the interparticle repulsion is sufficiently soft (n ≤ 7). For the model systems the phase boundary between the close-packed and the body-centered phases is located using lattice dynamics. The fluid—solid melting line is deduced from Monte Carlo computer experiments.