Browsing by Author "Chang, Yu-Hsien"

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3D Vision for Object Grasp and Obstacle Avoidance of a Collaborative Robot
(2019-01-01)
Song, Kai-Tai
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Chang, Yu-Hsien
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Chen, Jen-Hao
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電控工程研究所
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Institute of Electrical and Control Engineering
This paper presents a design and experimental study of 3D robotic vision for bin picking and obstacle avoidance. Through the 3D vision algorithm, the robotic picking system is able to analyze the imagery of cluttered objects, classify the objects and estimate the pose of identified objects for grasping. In order to facilitate the robot to work with a human nearby, obstacle avoidance during task execution is developed based on 3D vision. In this design, a RealSense SR300 RGB-D camera is utilized to acquire RGB images and depth images of clustered workpieces. A deep neural network (DNN) approach to object recognition is designed and combined with point cloud segmentation to enhance 3D object-pose estimation for grasping. The robot avoids obstacles to assure safe operation during execution of the bin picking task. Practical experiments using a Techman TM5 6-DOF robot arm show that the proposed method effectively accomplishes obstacle avoidance in pick-and-place operations.
Broadband Microstrip Impedance Transformer
(2016)
Kuo, Jen-Tsai
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Chang, Yu-Hsien
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Chung, Shyh-Jong
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電信工程研究所
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Institute of Communications Engineering
A broadband impedance transformer is proposed for microstrip realization and to release the tight gap size (30 mu m) required for coupled-stripline. Design curves of the transformer are obtained by solving the analytical equations derived from the transmission line theory. Two transformers are fabricated and measured. One is designed for a 1: 2 ratio and return loss better than 30 dB over a fractional bandwidth Delta=68%, and the other is a 1: 2.8 transformer with vertical bar S-11 vertical bar < -25 dB over a bandwidth of Delta = 71%. In realization, the metal traces are folded so that the circuit sizes are less than lambda/8x lambda/8. Good agreement between measured and simulation is obtained.
The economic value of co-movement between oil price and exchange rate using copula-based GARCH models
(2012-01-01)
Wu, Chih-Chiang
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Chung, Huimin
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Chang, Yu-Hsien
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
The US dollar is used as the primary currency of international crude oil trading; as such, the recent substantial depreciation in the US dollar has resulted in a corresponding increase in crude oil prices. In addition, oil price and exchange-rate returns have been shown to be skewed and leptokurtic, and to exhibit an asymmetric or tail dependence structure. Therefore, this study proposes dynamic copula-based GARCH models to explore the dependence structure between the oil price and the US dollar exchange rate. More importantly, an asset-allocation strategy is implemented to evaluate economic value and confirm the efficiency of the copula-based GARCH models. In terms of out-of-sample forecasting performance, a dynamic strategy based on the CGARCH model with the Student-t copula exhibits greater economic benefits than static and other dynamic strategies. In addition, the positive feedback trading activities are statistically significant within the oil market, but this information does not enhance the economic benefits from the perspective of an asset-allocation decision. Finally, a more risk-averse investor generates a higher fee for switching from a static strategy to a dynamic strategy based on copula-based GARCH models. (C) 2011 Elsevier B.V. All rights reserved.