Object pose estimation using multimodal sensor and object priors물체 정보와 멀티 모달 센서를 이용한 물체 자세 추정

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As robotic systems advance, it has been issued to manipulate various types of objects in various environment scenarios using the same robotic platform. To do that, estimating poses of objects is the pose important problem. However, robust object pose estimation in various types of environment is challenging problem. In the present thesis, I suggest robust pose estimation methods for different types of objects by using a multi-modal sensor system, an integration of RGB camera and 3D scanner. More specifically, pose estimation methods for door handles, debris, and rigid body objects are suggested. The suggested methods employed minimal human interaction in multimodal data space as well as objects priors. In addition, the 2D/3D calibration method is suggested to integrate the two sensors. The results of the experiments demonstrate the robustness of the proposed methods. Moreover, as a real-world application the suggested methods is employed as the vision system of a complete full size humanoid robot. The practical demos further validate the robustness and performance of the proposed methods.
Advisors
Kim, Dae-Shikresearcher김대식
Description
한국과학기술원 : 전기및전자공학과,
Publisher
한국과학기술원
Issue Date
2014
Identifier
569279/325007  / 020123581
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전기및전자공학과, 2014.2, [ 53 p. ]

Keywords

2D/3D calibration; multimodal sensor; 자세 추정; 2차원-3차원 교정; pose estimation; 멀티 모달 센서

URI
http://hdl.handle.net/10203/196807
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=569279&flag=dissertation
Appears in Collection
EE-Theses_Master(석사논문)
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