• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1106-1114
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• 2012

To achieve synchronized motion between a wearable robot and a human user, the redundancy must be resolved in the same manner by both systems. According to the seven DOF (Degrees of Freedom) human arm model composed of the shoulder, elbow, and wrist joints, positioning and orientating the wrist in space is a task requiring only six DOFs. Due to this redundancy, a given task can be completed by multiple arm configurations, and thus there exists no unique mathematical solution to the inverse kinematics. This paper presents analysis on the kinematic and dynamic aspect of the human arm movement and their effect on the redundancy resolution of the human arm based on a seven DOF manipulator model. The redundancy of the arm is expressed mathematically by defining the swivel angle. The final form of swivel angle can be represented as a linear combination of two different swivel angles achieved by optimizing different cost functions based on kinematic and dynamic criteria. The kinematic criterion is to maximize the projection of the longest principal axis of the manipulability ellipsoid for the human arm on the vector connecting the wrist and the virtual target on the head region. The dynamic criterion is to minimize the mechanical work done in the joint space for each two consecutive points along the task space trajectory. As a first step, the redundancy based on the kinematic criterion will be thoroughly studied based on the motion capture data analysis. Experimental results indicate that by using the proposed redundancy resolution criterion in the kinematic level, error between the predicted and the actual swivel angle acquired from the motor control system is less than five degrees.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.1
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• pp.67-72
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• 2015

The system for controlling the robotic arm through the foot motion detection was implemented for the disabled who not free to use of the arm. In order to get an image on foot movement, two cameras were setup in front of both foot. After defining multiple regions of interest by using LabView-based Vision Assistant from acquired images, we could detect foot movement based on left/right and up/down edge detection within the left/right image area. After transferring control data which was obtained according to left/right and up/down edge detection numbers from two foot images of left/right sides through serial communication, control system was implemented to control 6-joint robotic arm into up/down and left/right direction by foot. As a result of experiment, we was able to get within 0.5 second reaction time and operational recognition rate of more 88%.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1675-1678
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• 2004

In this paper, web based monitoring systems are implemented for multi-axis force control systems of an intelligence robot. A brief review about the principle of multi-axis force sensors and a method that can reduce the effect of noise signal to sensor performance is presented. A web based monitoring system is implemented by porting Linux at embedded systems which include Xscale processors. A device driver is developed to receive data from multi-axis force sensors in Linux operation systems. To control this device driver, a socket program for web browser is also developed. The experiments are performed to investigate the effectiveness of proposed methods. The experimental results show that the values of force sensors can be monitored by remote PCs.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.441-444
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• 1988

This paper presents a methodology for developing the graphic simulator for a robotic workcell. The Petri Net model is applied to described the system state and the workcell simulation is performed by the event scheduling approach of the model. For the graphic display of simulation process, the information of the workcell resources are stored in hierachically-structured data_babe, and the geometry of the resources is described by robot modelling, component modelling, and world modelling.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.3072-3074
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• 2005

In this paper, web based monitoring systems are implemented for multi-axis force control systems of an intelligence robot. A web based monitoring system is implemented by porting Linux at embedded systems which include a Xscale processor. A device driver is developed to receive data from multi-axis force sensors in Linux operation systems. To control this device driver, a socket program for the Labview is also developed.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.18-24
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• 2010

In this paper, we address an active ranging system based on laser structured light image for mobile robot application. Since the burdensome correspondence problem is avoidable, the structured light image processing has efficient computation in comparison with the conventional stereo image processing. By using a cylindrical lens in the laser generation, it is possible to convert a point laser into a stripe laser without motorized scan in the proposed system. In order to achieve robustness against environmental illumination noise, we propose an efficient integro-differential image processing algorithm. The proposed system has embedded image processing module and transmits distance data to reduce the computational burden in main control system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.871-872
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• 2014

In this paper, I propose the method of cooperative work of swarm robot for escaping maze. The robots can communicate with each other using Zigbee, but the central control system send commands to robots because of low processing power of robots. Robots navigate the blinded maze and send information such as movement to the central control system for building map. The central control system analysis the received data and find path to escape from maze.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.730-744
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• 2023

The topic of this paper is the recognition of human activities using egocentric vision, particularly captured by body-worn cameras, which could be helpful for video surveillance, automatic search and video indexing. This being the case, it could also be helpful in assistance to elderly and frail persons for revolutionizing and improving their lives. The process throws up the task of human activities recognition remaining problematic, because of the important variations, where it is realized through the use of an external device, similar to a robot, as a personal assistant. The inferred information is used both online to assist the person, and offline to support the personal assistant. With our proposed method being robust against the various factors of variability problem in action executions, the major purpose of this paper is to perform an efficient and simple recognition method from egocentric camera data only using convolutional neural network and deep learning. In terms of accuracy improvement, simulation results outperform the current state of the art by a significant margin of 61% when using egocentric camera data only, more than 44% when using egocentric camera and several stationary cameras data and more than 12% when using both inertial measurement unit (IMU) and egocentric camera data.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.334-343
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• 2001

Polishing a die that has free-form surfaces is a time-consuming and tedious job, and requires a considerable amount of high-precision skill. Some workers tend to gradually avoid the polishing work because of the poor environment caused by dust and noise. In order to reduce the polishing time and cope with the shortage of skilled workers, a user-friendly automatic polishing system was developed in this research. The polishing system with five degrees of freedom is able to keep the polishing tool normal to the die surface. The polishing system is controlled by a PC-NC controller. To easily operate the developed polishing robot system, this study developed an integrated program in the Windows environment. This program consists of four modules: the polishing module, the graphic simulator, the polishing data generation module, and the teaching module. Also, the automatic teaching system was developed to easily obtain teaching data and it consists of a three dimensional joystick and a proximity sensor. The joystick is used to simultaneously drive the polishing system to an arbitrary orientation and the proximity sensor is used to obtain teaching points precisely. Also, to evaluate the stability of the driving program and the teaching system, polishing experiments of a die of saddle shape were carried out.