電機工程學系
Permanent URI for this communityhttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/85
歷史沿革
本系成立宗旨在整合電子、電機、資訊、控制等多學門之工程技術，以培養跨領域具系統整合能力之電機電子科技人才為目標，同時配合產業界需求、支援國家重點科技發展，以「系統晶片」、「多媒體與通訊」、與「智慧型控制與機器人」等三大領域為核心發展方向，期望藉由學術創新引領產業發展，全力培養能直接投入電機電子產業之高級技術人才，厚植本國科技產業之競爭實力。
本系肇始於民國92年籌設之「應用電子科技研究所」，經一年籌劃，於民國93年8月正式成立，開始招收碩士班研究生，以培養具備理論、實務能力之高階電機電子科技人才為目標。民國96年8月「應用電子科技學系」成立，招收學士班學生，同時間，系所合一為「應用電子科技學系」。民國103年8月更名為「電機工程學系」，民國107年電機工程學系博士班成立，完備從大學部到博士班之學制規模，進一步擴展與深化本系的教學與研究能量。
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Item Localization of Mobile Robots Based on Omni-Directional Ultrasonic Sensing(2011-09-18) Chen-Chien Hsu; Chien-Yu Lai; Chisato Kanamori; Hisayuki; Aoyama; Ching-Chang WongA localization method based on omni-directional ultrasonic sensing is proposed in this paper, circumventing the detection-angle limitation of ultrasonic signals. Experiment setup includes four ultrasonic sensors located on the vertexes in a square environment serving as receivers and a mobile robot carrying an omni-directional ultrasonic device as a transmitter. Each ultrasonic sensor is integrated with a Zig-Bee module for communication. By sequential ultrasonic signal transmission between the robot and the receivers, the ultrasonic sensors can then measure the time-of-flight (TOF) while avoiding interference to calculate the distance between the receiver and transmitter ends. According to an established two-dimensional coordinate model using dual-circle derivation, the coordinate of the robot can be obtained based on the distance measurement. Experimental results have shown a satisfactory accuracy of the coordinates of the mobile robot via the proposed localization scheme.Item Localization of Mobile Robots via an Enhanced Particle Filter(2010-05-06) Chen-Chien Hsu; Ching-Chang Wong; Hung-Chih Teng; Nai-Jen Li; Cheng-Yao HoA self-localization method entitled enhanced particle filter incorporating tournament selection and Nelder-Mead simplex search (NM-EPF) for autonomous mobile robots is proposed in this paper. To evaluate the performance of the localization scheme, an omnidirectional vision device is mounted on top of the robot to analyze the environment of a soccer robot game field. Through detecting the white boundary lines relative to the robot in the game field, weighting for each particle representing the robot's pose can be updated via the proposed NM-EPF algorithm. Because of the efficiency of the NM-EPF, particles converge to the correct location of the robot in a responsive way while tackling uncertainties. Simulation results have shown that efficiency in robot self-localization can be significantly improved while maintaining a relatively smaller mean error in comparison to that via conventional particle filter.Item Hardware/Software Co-design for Particle Swarm Optimization Algorithm(2010-10-13) Shih-An Li; Chen-Chien Hsu; Ching-Chang Wong; Chia-Jun YuThis paper presents a hardware/software (HW/SW) co-design approach using SOPC technique and pipeline design method to improve the performance of particle swarm optimization (PSO) for embedded applications. Based on modular design architecture, a particle updating accelerator module via hardware implementation for updating velocity and position of particles and a fitness evaluation module implemented on a soft-cored processor for evaluating the objective functions are respectively designed and work closely together to accelerate the evolution process. Thanks to a flexible design, the proposed approach can tackle various optimization problems of embedded applications without the need for hardware redesign. To compensate the deficiency in generating truly random numbers by hardware implementation, a particle re-initialization scheme is also presented in this paper to further improve the execution performance of the PSO. Experiment results have demonstrated that the proposed HW/SW co-design approach to realize PSO is capable of achieving a high-quality solution effectively.Item Dual-Circle Self-Localization of Autonomous Soccer Robots with Omnidirectional Vision Robotics and Autonomous Systems(Taylor & Francis, 2012-06-01) Chen-Chien Hsu; Ching-Chang Wong; Hung-Chih Teng; Cheng-Yao HoA self-localization method entitled Dual-Circle Self-Localization (DCSL) for mobile robots in a soccer robot game filed is proposed in this paper. To evaluate the performance of the proposed localization method, an omnidirectional vision device is installed on top of the robot to capture images for recognizing objects in the environment via a hybrid scanning method. Three reliable objects recognized are then chosen as landmarks to calculate the position of the robot in the game field via the proposed DCSL based on relative positions between the robot and landmarks in the omnidirectional images. Because simple geometric manipulations are only required via the DCSL algorithm, localization efficiency can be significantly improved while maintaining a relatively smaller mean error in comparison to Monte Carlo Localization techniques as demonstrated in both simulation results and practical experiments in this paper.Item Localization of Mobile Robots via an Enhanced Particle Filter Incorporating Tournament Selection and Nelder-Mead Simplex Search(ICIC International, 2011-07-01) Chen-Chien Hsu; Ching-Chang Wong; Hung-Chih Teng; Cheng-Yao HoA localization method based on an enhanced particle lter incorporating tour- nament selection and Nelder-Mead simplex search (NM-EPF) for autonomous mobile robots navigating in a soccer robot game eld is proposed in this paper. To analyze the environment, an omnidirectional vision device is mounted on top of the robot. Through detecting the white boundary lines relative to the robot in the game eld, weighting for each particle representing the robot's pose can be iteratively updated via the proposed NM-EPF algorithm. Thanks to the hybridization effect of the NM-EPF, particles con- verge to the actual position of the robot in a responsive way while tackling uncertainties. Simulation and experiment results have con rmed that the proposed NM-EPF has better localization performance in the soccer robot game eld in comparison to the conventional particle lterItem Hardware/Software Co-design for Particle Swarm Optimization Algorithm(Elsevier, 2011-10-15) Shih-An Li; Chen-Chien Hsu; Ching-Chang Wong; Chia-Jun YuThis paper presents a hardware/software (HW/SW) co-design approach using SOPC technique and pipeline design method to improve design flexibility and execution performance of particle swarm optimization (PSO) for embedded applications. Based on modular design architecture, a Particle Updating Accelerator module via hardware implementation for updating velocity and position of particles and a Fitness Evaluation module implemented either on a soft-cored processor or Field Programmable Gate Array (FPGA) for evaluating the objective functions are respectively designed to work closely together to carry out the evolution process at different design stages. Thanks to the design flexibility, the proposed approach can tackle various optimization problems of embedded applications without the need for hardware redesign. To further improve the execution performance of the PSO, a hardware random number generator (RNG) is also designed in this paper in addition to a particle re-initialization scheme to promote exploration search during the optimization process. Experimental results have demonstrated that the proposed HW/SW co-design approach for PSO algorithms has good efficiency for obtaining high-quality solutions for embedded applications.Item Dual-Circle Self-Localization Algorithm for Omnidirectional Vision Robots(Harbin Institute of Technology, 2008-07-01) Chen-Chien Hsu; Ching-Chang Wong; Hung-Chih TengThis paper proposes a new self-localization algorithm, called dual-circle self-localization algorithm, for use in omnidirectional vision robots. When an autonomous robot navigates in the field, it senses the environment by an omnidirectional vision device fitted on the robot. The landmarks information is acquired by using image processing and pattern recognition techniques. Robot position on the field can be estimated with the proposed method by using these landmarks information. Comparing with other self-localization methods, the dual-circle self-localization algorithm requires only three landmarks information in the image for identifying the robot position, which is very efficient for image processing. Practical experiments on an autonomous robot have demonstrated that the proposed algorithm can achieve a satisfactory performance to locate the robot.