Jin, Yixiang ORCID: https://orcid.org/0000-0001-6286-278X
(2022)
An intelligent robotic vision system with environment perception.
PhD thesis, University of Sheffield.
Abstract
Ever since the dawn of computer vision[1, 2], 3D environment reconstruction and object 6D pose estimation have been a core problem. This thesis attempts to develop a novel 3D intelligent robotic vision system integrating environment reconstruction and object detection techniques to solve practical problems. Chapter 2 reviews current state-of-the art of 3D vision techniques from environment reconstruction and 6D pose estimation.In Chapter 3 a novel environment reconstruction system is proposed by using coloured point clouds. The evaluation experiment indicates that the proposed algorithm 2 is effective for small-scale and large scale and textureless scenes. Chapter 4 presents Image-6D (that is section 4.2), a learning-based object pose estimation algorithm from a single RGB image. Contour-alignment is introduced as an efficient algorithm for pose refinement in an RGB image. This new method is evaluated on two widely used benchmark image data bases, LINEMOD and Occlusion-LINEMOD. Experiments show that the proposed method surpasses other state-of-the-art RGB based prediction approaches. Chapter 5 describes Point-6D (defined in section 5.2), a novel 6D pose estimation method using coloured point clouds as input. The performance of this new method is demonstrated on LineMOD [3] and YCB-Video [4] dataset. Chapter 6 summarizes contributions and discusses potential future research directions. In addition, we presents an intelligent 3D robotic vision system deployed in a simulated/laboratory nuclear waste disposal scenario in Appendices B. To verify the results, a simulated nuclear waste handling experiment has been successfully completed via the proposed robotic system.
Metadata
Supervisors: | Rossiter, Anthony and Veres, Sandor |
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Keywords: | 6D pose estimation, 3D robotic vision, 3D object detection, environment perception |
Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Automatic Control and Systems Engineering (Sheffield) |
Identification Number/EthosID: | uk.bl.ethos.861142 |
Depositing User: | Mr Yixiang Jin |
Date Deposited: | 30 Aug 2022 07:45 |
Last Modified: | 01 Oct 2022 10:01 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:31259 |
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