Browsing by Author "Wu, Chin-Chia"

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A Procedure for Simultaneous Calibration of Environmental Cameras and Localization of Mobile Robots
(2009)
Hsieh, Hsiang-Wen
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Wu, Chin-Chia
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Hu, Jwu-Sheng
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電控工程研究所
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Institute of Electrical and Control Engineering
With an accurate estimate of the robot pose, robots will be capable of navigating in the environment autonomously and efficiently. In this paper, an infrastructure comprises of simultaneous camera calibration and robot localization is presented. The presented approach utilizes particle filter that integrates odometry data from robot and images captured from overhead cameras in the environment to localize the robot and calibrate overhead camera. An odometry-based motion model, HSV histogram-based measurement model and DLT (Direct Linear Transform) are designed to estimate robot poses and calibration cameras iteratively. Experiment results show the presented approach could calibrate the camera and estimate robot poses iteratively with reprojection errors around 210 mm in world reference plane.
AN EFFICIENT 3D MODEL RETRIEVAL BASED ON PRINCIPAL AXES ANALYSIS AND FEATURE INTEGRATION
(2011-06-01)
Lin, Sheng-Fuu
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Wu, Chin-Chia
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Hsu, Chi-Yao
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Hsu, Dou-Chih
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電機工程學系
Three-dimensional (3D) model retrieval has gathered great importance in recent years, since the number of available 3D models on the Internet has drastically increased. Many content-based 3D model retrieval approaches have been proposed. Among these methods, visual similarity-based methods have shown higher retrieval accuracy. However, because these methods capture enormous shape features from different viewpoints or locations, a large amount of calculation and comparison is necessary. Furthermore, there is a trade-off between retrieval accuracy and speed. In this paper, a 3D model retrieval method constituting Continuous Principal Component Analysis (CPCA), Fourier descriptors, and Zernike moments is proposed. CPCA is applied to extract significant shape features based on projecting the model along the principal axes. Then, Fourier descriptors and Zernike moments are used to provide shape descriptors with rotation invariants. In addition, a feature integration process combines them. A strategy of similarity measure is proposed to solve the axes switching problem. To conclude, the experimental results show that the approach outperforms SECTORS(2) and D2,(18) and has slightly better retrieval results than Light Field Descriptor (LFD)(6) and spin-image signatures.(3) Moreover, the approach is more efficient and the storage size is much less.
Efficiency evaluation of bus transit firms with and without consideration of environmental air-pollution emissions
(2017-01)
Kang, Chao-Chung
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Khan, Haider A.
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Feng, Cheng-Min
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Wu, Chin-Chia
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運輸與物流管理系註：原交通所+運管所
This study examines the technical efficiency and environmental efficiency of bus transit firms using the slack-based measures (SBM) and non-separable slack-based measures (NSSBM) models with and without considerations of desirable and undesirable outputs. A case study based on data from 12 bus transit firms for the years 2007 to 2011 was conducted. Empirical results show that technical efficiency was affected by environmental pollution constraints from 2007 to 2011. The study has more general theoretical implications for the externalities literature as well. (C) 2016 Elsevier Ltd. All rights reserved.
Robust scheduling for a two-stage assembly shop with scenario-dependent processing times
(1970-01-01)
Wu, Chin-Chia
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Gupta, Jatinder N. D.
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Cheng, Shuenn-Ren
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Lin, Bertrand M. T.
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Yip, Siu-Hung
Recently, finding solutions to assembly flowshop scheduling problems is a topic of extensive discussion in research communities. While existing research assumes that job processing times are constant numbers, in several practical situations, due to several external factors like machine breakdowns, working environment changes, worker performance instabilities, and tool quality variations and unavailability, job processing times may vary. In this study, therefore, we address a two-stage assembly flowshop scheduling problem with two scenario-dependent jobs processing times to minimise the maximum makepsan among both scenarios (called robust makespan) In view of the NP-hard nature, we first derive a dominance property and a lower bound to propose a branch-and-bound algorithm to find a permutation schedule with minimum makespan. Following that, we use Johnson's rule to propose eight polynomial heuristics for finding near-optimal solutions. Furthermore, we propose four cloud theory-based simulated annealing (CSA) hyper-heuristic algorithms incorporating seven low level heuristics to solve a robust two-stage assembly flowshop problem with scenario-dependent processing times. Finally, we empirically evaluate the effectiveness of all the proposed algorithms in minimising the robust makespan.