A cybernetic approach to land management issues

This work is a digital version of a dissertation that was first submitted in partial fulfillment of the Degree of Doctor of Philosophy at the Queensland University of Technology (QUT) in March 1994. The work was concerned with problems of self-organisation and organisation ranging from local to global levels of hierarchy. It considers organisations as living entities from local to global things that a living entity – more particularly, an individual, a body corporate or a body politic - must know and do to maintain an existence – that is to remain viable – or to be sustainable. The term ‘land management’ as used in 1994 was later subsumed into a more general concept of ‘natural resource management’ and then merged with ideas about sustainable socioeconomic and sustainable ecological development. The cybernetic approach contains many cognitive elements of human observation, language and learning that combine into production processes. The approach tends to highlight instances where systems (or organisations) can fail because they have very little chance of succeeding. Thus there are logical necessities as well as technical possibilities in designing, constructing, operating and maintaining production systems that function reliably over extended periods. Chapter numbers and titles to the original thesis are as follows: 1. Land management as a problem of coping with complexity 2. Background theory in systems theory and cybernetic principles 3. Operationalisation of cybernetic principles in Beer’s Viable System Model 4. Issues in the design of viable cadastral surveying and mapping organisation 5. An analysis of the tendency for fragmentation in surveying and mapping organisation 6. Perambulating the boundaries of Sydney – a problem of social control under poor standards of literacy 7. Cybernetic principles in the process of legislation 8. Closer settlement policy and viability in agricultural production 9. Rate of return in leasing Crown lands

Spatial mapping and map exploitation : a bio-inspired engineering perspective

Probabilistic robot mapping techniques can produce high resolution, accurate maps of large indoor and outdoor environments. However, much less progress has been made towards robots using these maps to perform useful functions such as efficient navigation. This paper describes a pragmatic approach to mapping system development that considers not only the map but also the navigation functionality that the map must provide. We pursue this approach within a bio-inspired mapping context, and use esults from robot experiments in indoor and outdoor environments to demonstrate its validity. The research attempts to stimulate new research directions in the field of robot mapping with a proposal for a new approach that has the potential to lead to more complete mapping and navigation systems.

RatSLAM : a hippocampal model for simultaneous localization and mapping

The work presents a new approach to the problem of simultaneous localization and mapping - SLAM - inspired by computational models of the hippocampus of rodents. The rodent hippocampus has been extensively studied with respect to navigation tasks, and displays many of the properties of a desirable SLAM solution. RatSLAM is an implementation of a hippocampal model that can perform SLAM in real time on a real robot. It uses a competitive attractor network to integrate odometric information with landmark sensing to form a consistent representation of the environment. Experimental results show that RatSLAM can operate with ambiguous landmark information and recover from both minor and major path integration errors.

Probabilistic visual recognition of artificial landmarks for simultaneous localization and mapping

Probabilistic robotics, most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainly to accompany observations of the environment. This paper describes how uncertainly can be characterised for a vision system that locates coloured landmark in a typical laboratory environment. The paper describes a model of the uncertainly in segmentation, the internal camera model and the mounting of the camera on the robot. It =plains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainly model,