Geometry model for marker-based localisation

This work presents a novel approach for position estimation from monocularvision. It has been shown that vision systems have great capability in reaching precise and accurate measurements and are becoming the state-of-the-art innavigation. Navigation systems have only been integrated in commercial mobile robots since the early 2000s, and yet localisation in a dynamic environmentthat form the main building block of navigation, has no truly elegant solution.Solutions are many and their strategies and methods differ depending on theapplication. For the lack of a single accurate procedure, methods are combinedwhich make use of different sensors fusion. This thesis focus on the use of monocular vision sensor to develop an accurate Marker-Based positioning system thatcan be used in various applications in outdoor, in agriculture for example, andin other indoor applications. Many contributions arouse here in this context. Amain contribution is in perspective distortion correction in which distortions aremodeled in all its forms with correction process. This is essential when dealingwith measurements and shapes in images. Because of the lack of robustness indepth sensing using monocular vision-based system, a second contribution is inthe novel spherical marker-based approach position captured, which is designedand developed within the concept of relative pose estimation. In this Model-Basedposition estimation, relative position can be extracted instantaneously withoutthe need of prior knowledge of the previous state of the camera, as it relies onmonocular image. This model can as well compensate for the lack of knowledge inthe scale of the real world, for example in the case of Monocular Visual Simultaneous Localisation and Mapping (VSLAM). In addition to these contributions, someexperimental and simulation evidence presented in this work has shown feasibilityof the reading measurements like distance capture and relative pose between themarker-based model and the observer, with reliability and high accuracy. Thesystem has shown the ability to track accurately the object at a farthest possibleposition from low resolution digital images and from a single viewpoint. Whilethe main application field targeted is tracking mobile-robots, other applicationscan profit from this concept like motion capture and application related to thefield of topography.

Level dc:type.qualificationlevel

Doctoral (Level 8)

Year dc:date.issued

2020

Author dc:creator

• Bou Said Yssa, A

Language dc:language

en

Identifier

oai:salford-repository.worktribe.com:1352358

OAI identifier oai:identifier

oai:salford-repository.worktribe.com:1352358