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RISS 인기검색어
- 검색키워드
- 저자 : ( Thi Duyen Ngo ) (검색결과 3 건)
- 무료
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Duyen Ha Thi Kim,Tien Ngo Manh,Cuong Nguyen Manh,Nhan Duc Nguyen,Dung Pham Tien,Manh Tran Van,Minh Phan Xuan 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.4
The paper proposes the method to deal with control problems of unmodeled components of the fourwheeled Omni-directional mobile robot. It is commonly challenging to design a model-based control scheme to achieve smooth movement in the tracking process due to the unknown elements in the mathematical model of the robot or external disturbances. Our main contribution focuses on designing an adaptive controller based on neural networks with online weight updating laws and Fuzzy logic to guarantee the high accuracy of the robot’s movement when the unknown factors adversely affect the robot control. At the initial step, a Dynamic Surface Control plays a role as a core of the controller for the robot system. Then, with the ability to estimate the appropriate value for uncertain nonlinear parts, a Radial Basis Function Neural Network is designed. Finally, a Fuzzy law is to utilize control parameters in each period to increase the adaptive behavior of the system. The stability and convergence of the system are proven by the Lyapunov’s stability theory. The simulation results illustrate the validity and the efficiency of the proposed control algorithm when the system is lack of robot model’s information.
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A Spatial-Temporal Three-Dimensional Human Pose Reconstruction Framework
( Xuan Thanh Nguyen ),( Thi Duyen Ngo ),( Thanh Ha Le ) 한국정보처리학회 2019 Journal of information processing systems Vol.15 No.2
Three-dimensional (3D) human pose reconstruction from single-view image is a difficult and challenging topic. Existing approaches mostly process frame-by-frame independently while inter-frames are highly correlated in a sequence. In contrast, we introduce a novel spatial-temporal 3D human pose reconstruction framework that leverages both intra and inter-frame relationships in consecutive 2D pose sequences. Orthogonal matching pursuit (OMP) algorithm, pre-trained pose-angle limits and temporal models have been implemented. Several quantitative comparisons between our proposed framework and recent works have been studied on CMU motion capture dataset and Vietnamese traditional dance sequences. Our framework outperforms others by 10% lower of Euclidean reconstruction error and more robust against Gaussian noise. Additionally, it is also important to mention that our reconstructed 3D pose sequences are more natural and smoother than others.
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A Spatial-Temporal Three-Dimensional Human Pose Reconstruction Framework
Nguyen, Xuan Thanh,Ngo, Thi Duyen,Le, Thanh Ha Korea Information Processing Society 2019 Journal of information processing systems Vol.15 No.2
Three-dimensional (3D) human pose reconstruction from single-view image is a difficult and challenging topic. Existing approaches mostly process frame-by-frame independently while inter-frames are highly correlated in a sequence. In contrast, we introduce a novel spatial-temporal 3D human pose reconstruction framework that leverages both intra and inter-frame relationships in consecutive 2D pose sequences. Orthogonal matching pursuit (OMP) algorithm, pre-trained pose-angle limits and temporal models have been implemented. Several quantitative comparisons between our proposed framework and recent works have been studied on CMU motion capture dataset and Vietnamese traditional dance sequences. Our framework outperforms others by 10% lower of Euclidean reconstruction error and more robust against Gaussian noise. Additionally, it is also important to mention that our reconstructed 3D pose sequences are more natural and smoother than others.
KCI
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