• 전자공학회논문지S
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• 제35S권2호
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• pp.58-69
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• 1998

A contrp; suste, fpr SCARA robot is designed for implememting a robust dynamic control algorithm. this study forcuses on the use of DSPs in the design of joint controllers and interfaces in between the host cotroller and four joint controllers and in between the joint controllers and four servo drives. The mechanical body of SCARA robot and the servo drives are selected from the commercially available ones. The four joint controllers, assigned to each joint one by one, are combined into a common system through a mother board hardwarewise and through the global memeory softwarewise. The mother board is designed to connect joint controllers onto the board through the slots adopting PC/104 bus structures. And, the global memory stores the common data which can be shared by joint controllers and the host computer directly, which virtually combines the whole system into one. To demonstrate the performance and efficienty of the sytem, a robust inverse dynamic algorithm is proposed and implemented for a faster and more precise control. The robust inverse dynamic algorithm is basically derived from an inverse dynamci algorithm and a PID compensator. Based upon the derived dynamic equitions of SCARA robot, the inverse dynamic algorithm is intitially implemented within 0.3 msec of the control cycle in this system. The algoithm is found to be not accurate enough for the high speed and precision tasks due to inherent modelling errors and time-varying factors. Therefore, a variable PID algorithm is combined with the inverse dynamic algorithm to support robustness of control performance. Experimental datfor the proposed algorithm are presented and compared with the result obtained from PID and inverse dynamic algorithm.

• Journal of Information Processing Systems
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• 제17권4호
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• 한국통신학회논문지
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• 제22권6호
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• pp.1195-1209
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• 1997

This paper presents a new morphological spatio-temporal segmentation algorithm. The algorithm incorporates luminance and motion information simultaneously, and uses morphological tools such as morphological filtersand watershed algorithm. The procedure toward complete segmentation consists of three steps:joint marker extraction, boundary decision, and motion-based region fusion. First, the joint marker extraction identifies the presence of homogeneours regions in both motion and luminance, where a simple joint marker extraction technique is proposed. Second, the spatio-temporal boundaries are decided by the watershed algorithm. For this purposek, a new joint similarity measure is proposed. Finally, an elimination ofredundant regions is done using motion-based region function. By incorporating spatial and temporal information simultaneously, we can obtain visually meaningful segmentation results. Simulation results demonstratesthe efficiency of the proposed method.

• 한국정밀공학회지
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• 제29권9호
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• pp.986-994
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• 2012

This paper is concerned with the application of the vision control algorithm with weighting matrix in robot point placement task. The proposed vision control algorithm involves four models, which are the robot kinematic model, vision system model, the parameter estimation scheme and robot joint angle estimation scheme. This proposed algorithm is to make the robot move actively, even if relative position between camera and robot, and camera's focal length are unknown. The parameter estimation scheme and joint angle estimation scheme in this proposed algorithm have form of nonlinear equation. In particular, the joint angle estimation model includes several restrictive conditions. For this study, the weighting matrix which gave various weighting near the target was applied to the parameter estimation scheme. Then, this study is to investigate how this change of the weighting matrix will affect the presented vision control algorithm. Finally, the effect of the weighting matrix of robot vision control algorithm is demonstrated experimentally by performing the robot point placement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권1호
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• pp.395-405
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• 2012

A joint template matching algorithm is proposed in this paper to reduce the high rate of miss-detection and false-alarm caused by the traditional template matching algorithm during the process of multi-object detection. The proposed algorithm can reduce the influence on each object by matching all objects together according to the correlation information among different objects. Moreover, the rate of miss-detection and false-alarm in the process of single-template matching is also reduced based on the algorithm. In this paper, firstly, joint template is created from the information of relative positions among different objects. Then, matching criterion according to normalized cross correlation is generated for multi-object matching. Finally, the proposed algorithm is applied to the detection of watermarks in bill. The experiments show that the proposed algorithm has lower miss-detection and false-alarm rate comparing to the traditional NCC algorithm during the process of multi-object detection.

• 한국공작기계학회논문집
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• 제18권2호
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• pp.154-161
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• 2009

In order to implement continuous-path motion on a robot, it is necessary to blend one joint motion to another joint motion near a via point in a trapezoidal form of joint velocity. First, the velocity superposition using parametric interpolation is proposed. Hybrid motion blending is defined as the blending of different two type's motions such as blending of joint motion with linear motion, in the neighborhood of a via point. Second, hybrid motion blending algorithm is proposed based on velocity superposition using parametric interpolation. By using a 3-axis SCARA (Selective Compliance Assembly Robot Arm) robot with $LabVIEW^{(R)}$ $controller^{(1)}$, the velocity superposition algorithm using parametric interpolation is shown to result in less vibration, compared with PTP(Point- To-Point) motion and Kim's algorithm. Moreover, the hybrid motion $algorithm^{(2)}$ is implemented on the robot using $LabVIEW^{(R)(1)}$ programming, which is confirmed by showing the end-effector path of joint-linear hybrid motion.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 추계 학술발표회 논문집
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• pp.129-132
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• 2002

네트워크를 설계하거나 평가하는데 있어 중요한 문제 중 하나는 그 네트워크를 구성하는 요소들간의 상대적 중요도(importance)에 관한 문제이다. 이런 중요도를 나타내는 여러 가지 측도들 중 하나인 Joint Reliability Importance(JRI)는 Hong & Lie(1993)에 의해 소개되었으며, 네 가지 파생된 서브그래프의 신뢰성을 구하여 JRI를 계산하는 방법이 제시되었다. 본 연구에서는 minimal path set을 이용하여 파생되는 서브 그래프 신뢰성 계산에서의 중복되는 계산과정을 줄임으로써 JRI를 보다 효율적으로 구하는 방법을 제시하고자 한다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.707-711
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• 1999

In this paper, an algorithm of fault tolerant gaits for a quadruped robot is proposed for the purpose of tolerating a locked joint failure. The robot can continue its walking after a locked failure occurs to a joint of a leg by the proposed algorithm. In particular, a periodic gait is proposed as a special form of the proposed algorithm and its existence and efficiency are analytically proven.

• 한국정밀공학회지
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• 제28권6호
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• pp.670-677
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• 2011

This study is to estimate the joint torques without torque sensor using the EMG (Electromyogram) signal of agonist/antagonist muscle with Neural Network Back Propagation Algorithm during the elbow motion. Command Signal can be guessed by EMG signal. But it cannot calculate the joint torque. There are many kinds of field utilizing Back Propagation Learning Method. It is generally used as a virtual sensor estimated physical information in the system functioning through the sensor. In this study applied the algorithm to obtain the virtual senor values estimated joint torque. During various elbow movement (Biceps isometric contraction, Biceps/Triceps Concentric Contraction (isotonic), Biceps/Triceps Concentric Contraction/Eccentric Contraction (isokinetic)), exact joint torque was measured by KINCOM equipment. It is input to the (BP)algorithm with EMG signal simultaneously and have trained in a variety of situations. As a result, Only using the EMG sensor, this study distinguished a variety of elbow motion and verified a virtual torque value which is approximately(about 90%) the same as joint torque measured by KINCOM equipment.

• 로봇학회논문지
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• 제9권1호
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• pp.11-19
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• 2014

In this paper, an external torque estimation problem in one-degree-of-freedom (1-DOF) flexible-joint robot equipped with a joint-torque sensor is revisited. Since a sensor torque from the joint-torque sensor is distorted by two dynamics having a spring connection, i.e., motor dynamics and link dynamics of a flexible-joint robot, a model-based estimation, rather than a simple linear spring model, should be required to extract external torques accurately. In this paper, an external torque estimation algorithm for a 1-DOF flexible-joint robot is proposed. This algorithm estimates both an actuating motor torque from the motor dynamics and an external link torque from the link dynamics simultaneously by utilizing the flexible-joint robot model and the Kalman filter estimation based on random-walk model. The basic structure of the proposed algorithm is explained, and the performance is investigated through a custom-designed experimental testbed for a vertical situation under gravity.