Geometry model for marker-based localisation

Bou Said Yssa, A 2019, Geometry model for marker-based localisation , PhD thesis, University Of Salford.

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This work presents a novel approach for position estimation from monocular vision. It has been shown that vision systems have great capability in reaching precise and accurate measurements and are becoming the state-of-the-art in navigation. Navigation systems have only been integrated in commercial mobile robots since the early 2000s, and yet localisation in a dynamic environment that form the main building block of navigation, has no truly elegant solution. Solutions are many and their strategies and methods differ depending on the application. For the lack of a single accurate procedure, methods are combined which make use of different sensors fusion. This thesis focus on the use of monocular vision sensor to develop an accurate Marker-Based positioning system that can be used in various applications in outdoor, in agriculture for example, and in other indoor applications. Many contributions arouse here in this context. A main contribution is in perspective distortion correction in which distortions are modeled in all its forms with correction process. This is essential when dealing with measurements and shapes in images. Because of the lack of robustness in depth sensing using monocular vision-based system, a second contribution is in the novel spherical marker-based approach position captured, which is designed and developed within the concept of relative pose estimation. In this Model-Based position estimation, relative position can be extracted instantaneously without the need of prior knowledge of the previous state of the camera, as it relies on monocular image. This model can as well compensate for the lack of knowledge in the scale of the real world, for example in the case of Monocular Visual Simultaneous Localisation and Mapping (VSLAM). In addition to these contributions, some experimental and simulation evidence presented in this work has shown feasibility of the reading measurements like distance capture and relative pose between the marker-based model and the observer, with reliability and high accuracy. The system has shown the ability to track accurately the object at a farthest possible position from low resolution digital images and from a single viewpoint. While the main application field targeted is tracking mobile-robots, other applications can profit from this concept like motion capture and application related to the field of topography.

Item Type: Thesis (PhD)
Contributors: Nefti-Meziani, S (Supervisor)
Schools: Schools > School of Computing, Science and Engineering
Funders: University of Salford, EU Commision's FP7 Marie Curie Programme
Depositing User: Alexandre Bou Said Yssa
Date Deposited: 10 Nov 2020 08:46
Last Modified: 27 Aug 2021 21:45

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