In mobile robotics, visual perception in unknown environments consists mainly of two tasks: generation of a map and localization of the agent within it, using images as input. This problem is commonly called Visual Simultaneous Localization and Mapping ( Visual SLA M). This project aims of increasing the capacities of spatial reasoning in robotics systems based on cognitive vision. Baycsian formulation of visual mapping is extended to consider geometric properties for increasing of scene understand- ing. In this search, this work presents a framework that covers the computa- tional and algorithmic perspectives in Cognitive Vision. proposed by Marr. A part of the work is devoted to develop the representational framework for describing the visual phenomenon in monocular SLAM, unifying concepts about the existent parametrization and extending the analysis to geometric properties and relations in the scene. This yields a novel strategy for aug- mented mapping with high lcvellandmarks based on planar surfaces. After, we explore the computational level of visual SLAM through a sym- bolic framework for describing the elements required for spatial reasoning, involved in visual SLAM. An ontology for spatial reasoning is proposed upon visual SLAM context. An axiomatic set in visual scenario is related to prop- erties in projective geometry, assuring a scheme for semantic attachment. Finally, a novel approach to solve visual SLAM based on spatial reasoning is presented, focusing on the algorithmic level. The model of latent geomet- ric constraints is presented as a non-parametric Baycsian extension of visual SLAM. The generative model produces multiples scenarios with different visual conditions. Although this thesis is focused on solving visual SLAM, the proposed ap- proach can be conceived as a methodology for the design of cognitive dynamic systems.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:575461 |
| Date | January 2012 |
| Creators | Barron-Gonzalez, Hector |
| Publisher | University of Sheffield |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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