When applied to rapidly moving objects with complex trajectories, the information-rate limitation imposed by video-camera frame rates impairs the effectiveness of structured-light techniques in real-time robot servoing. To improve the performance of such systems, the use of fast infra-red proximity detectors to augment visual guidance in the final phase of target acquisition was explored. It was found that this approach was limited by the necessity of employing a different range/intensity calibration curve for the proximity detectors for every object and for every angle of approach to complex objects. Consideration of the physics of the detector process suggested that a single log-linear parametric family could describe all such calibration curves, and this was confirmed by experiment. From this result, a technique was devised for cooperative interaction between modalities, in which the vision sense provided on-the-fly determination of calibration parameters for the proximity detectors, for every approach to a target, before passing control of the system to the other modality. This technique provided a three hundred percent increase in useful manipulator velocity, and improved performance during the transition of control from one modality to the other.

After elucidating the terms ‘mining’ and ‘robot’, a historical background to the problem of mining is described, with emphasis on the use of technology. Various reasons for the increasing utilisation of technology are discussed, as regards the mechanisation of existing operations and those unachievable without new technology. It is asserted that the mining industry has a number of particular features that make increasing mechanisation especially attractive. The point is made that the ultimate stage of the historical tendency towards the use of new technology is fully automatic mining, a goal that may not be realised, however, in the next decade.

The above historical discussion is followed by a critical appraisal of the conservative nature of the Australian industry and the study of the various factors that contribute to the slow uptake of new technology in mining.

Attention is then concentrated on the general problem of robots and mining. It is shown that worldwide there were no applications of robots to mining up to the end of 1981. A wide study has been carried out to identify some uses of robots in mining, but without success.

The next topic to be discussed is the widespread confusion about robots and teleoperators. The fundamental difference between the two is underlined, and particular attention is paid to Thring's teleoperator mining concept (telechiric mining). It is emphasized that telechiric mining will have no significant impact upon Australian mining in this decade.

These pessimistic asssessments are followed by claims that in some areas robotic concepts, though not robots themselves, could have a considerable effect on mining automation in the 1980's, both in Australia and elsewhere. The following projects are enumerated as possible candidates for applying robotic concepts: Surface mining; Mine development; Underground coal transport; Coal winning; Coal preparation. In order to make progress, it is recommended that a robotics expert ought to be included in the interdisciplinary teams studying the problem of mining automation.

The last part of this paper is devoted to Australia's need for robotic mining. A list of systems involving robotic concepts is presented that may be realised in the current decade. It is maintained that Australia ought to develop a few of such systems for the domestic and international markets, and that the short-term needs of the Australian mining industry are fundamentally different from those of other Australian industries as regards robots. Hence, decisions regarding robots for mining should be made independently from those appertaining to automation problems of other industries.

This paper compares three numerical methods for obtaining the joint trajectory of a robot manipulator, which causes movement along the desired Cartesian path. The first solves the kinematic equations, which are given in the Jacobian form, while the other two solve the nonlinear kinematic equations directly by using an iterative computational procedure based on the conjugate gradient technique. The computational efficiency of the proposed methods is estimated in terms of the execution time on a VAX 11/750 minicomputer. It is shown that by using the capacity of microcomputers, these methods could be well used in real-time computation.

The major thrust of technological development is the reduction of the demands made by I.T. equipment on its users. The economic pressures which underpin such developments are based on 2 principles: the continuing fall of the cost of processing power (but particularly storage) and the market edge of simple as opposed to complex systems.

The techniques which can no longer be disregarded include voice and vision communication which frees the users' hands from the prison of the keyboard: also the logical power of IT equipment will not only extend excellence of rigorous reasoning, but also the type of person to person reasoning which takes the human factor into account.

Cybernetic techniques already ensure that computing machines are produced efficiently. Consideration is now given to the case for automating the means of producing computer software. A formal notation to describe software production is outlined and some machine portable systems are introduced. New and powerful techniques for modelling machines and producing ‘program’ generators are described.

It has become a truism that the introduction of modern technology requires new skills from both management and workforce. Yet recent reports confirm that the supply of trained manpower is failing to match present and future demand. Government action may be required, but more important is the need to promote greater liaison between higher education and industry, and to move - at craft and technician level - to a standard of training already being achieved by our competitors overseas. To accomplish these objectives requires a change in our attitude to education and training.

A simple general model for learning, using a fuzzy set theoretic approach and fuzzy decision in an automaton which has nonfuzzy input/output, is proposed. The process has been modelled somewhat in the fashion of general biological systems, which may be viewed as a fuzzy decision process where learning consists in taking a tentative action and reinforcing the membership values on the basis of the results of that action. The model is tested on an automaton whose sole purpose is to follow the boundary on an object with which it makes contact during its movements. The automaton is simulated by a computer. it has standard 8–neighbourhood configuration with binary sense capability and three action capabilities. The automaton has been found to learn to take correct action in a large number of possible input situations within only a few thousand moves.