Bryan Gardiner

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Machine learning enables the creation of a nonlinear mapping that describes robot-environment interaction, whereas computing linguistics make the interaction transparent. In this paper, we develop a novel application of a linguistic decision tree for a robot route learning problem by dynamically deciding the robot's behavior, which is decomposed into atomic(More)
In recent years, the processing of hexagonal pixel-based images has been investigated, and as a result, a number of edge detection algorithms for direct application to such image structures have been developed. We build on this paper by presenting a novel and efficient approach to the design of hexagonal image processing operators using linear basis and(More)
As features within an image may be present at many scales, application of feature detectors at multiple scales can improve accuracy of the detected localisation and orientation. As the scale and size of a feature detector increases, so does the computational complexity of implementation across the image domain. To address this issue we present a novel(More)