• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.55.3-55
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• 2001

The implementation of human-like robot has been advanced in various parts such as mechanic arms, legs, and applications of five senses. The vision applications have been developed in several decades and especially the face recognition have become a prominent issue. In addition, the development of computer systems makes it possible to process complex algorithms in realtime. The most of human recognition systems adopt the discerning method using fingerprint, iris, and etc. These methods restrict the motion of the person to be discriminated. Recently, the researchers of human recognition systems are interested in facial recognition by using machine vision. Thus, the object of this paper is the implementation of the realtime ...

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2123-2130
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• 2015

For such automatic monitoring robot or a robot cleaner that is utilized indoors, if it deviates from someone by replacement or, or of a mobile robot such as collisions with unexpected object direction or planned path, based on the planned path There is a need to come back to, it is necessary to tough self-position estimation ability of mobile robot in this, which is also associated with resolution of the kidnap problem of conventional mobile robot. In this study, the case of a mobile robot, operates indoors, you want to take advantage of the low cost of the robot. Therefore, in this paper, by using the acquisition device to an external image information such as the CCTV which is installed in a room, it acquires the environment image and take advantage of marker recognition of the mobile robot at the same time and converted it absolutely spatial coordinates it is, we are trying to solve the self-position estimation of the mobile robot in the room and kidnap problem and actual implementation methods potential field to try utilizing robotic systems. Thus, by implementing the method proposed in this study to the actual robot system, and is promoting the relevant experiment was to verify the results.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.624-631
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• 2008

This paper presents a method for a mobile robot to follow a moving object in real time. The robot follows a target object keeping the facing angle toward the target and the distance to the target to given value. The method consists of two procedures: first, the detection of target position in the robot coordinate system, and the second, the calculation of translational velocity and rotational velocity to follow the object:. To detect the target location, range sensor data is represented in histogram. Based on the real time calculation of the location of the target relative to the robot, translational velocity and rotational velocity to follow the target are calculated. The velocities make the heading angle and the distance to target converge toward the desired ones. The performance of the method is tested through simulation. In the simulation, the target moves with three different trajectories, straight line trajectory, rectangular trajectory, and circular trajectory. As shown in the results, it is inevitable to lose track temporarily of the target when the target suddenly changes its motion direction. Nevertheless, the robot speeds up to catch up and finally succeeds to follow the target as soon as possible even in this case. The proposed method can also be utilized to coordinate the motion of multiple robots to keep their formation as well as to follow a target.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.438-444
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• 2004

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Since the equations are based or the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied for this method. its performance is verified by the computer simulation and the experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.658-663
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• 2012

An accurate outdoor localization method using line/arc features is suggested for mobile robots with LRFs (Laser Range Finders) and odometry. Localization is a key process for outdoor mobile robots which are used for autonomous navigation, exploration and so on. In this paper, an accurate pose correction algorithm is proposed for mobile robots using LRFs, which use three feature types: line, circle, and arc. Using this method we can reduce the number of singular cases that robots couldn't find their pose. Finally we have got simulation results to validate the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.481-485
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• 2014

In service robots, a number of human movements are analyzed using a variety of sensors. Vibration signals from walking movements of a human provide useful information about the distance and the movement direction of the human. In this paper, we measure the intensity of vibrations and detect both human walking pace and direction. In our experiments, vibration signals detected by microphone sensors provide good estimation of the distance and direction of a human movement. This can be applied to HRI (Human-Robot Interaction) technology.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.468-472
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• 2013

This paper deals with the indoor localization problem for a SSMR (Skid Steering Mobile Robot) subjected to wheel-ground friction and with one LRF (Laser Range Finder). In order to compensate for some friction effect, a friction related coefficient is estimated by the recursive least square algorithm and appended to the maneuvering command. Also to reduce odometric information based localization errors, the lines are extracted with scan points of LRF and matched with the ones of the corresponding map built in advance. The present friction compensation and scan map matching schemes have been applied to a laboratory SSMR, and experimental results are given to validate the localization performance along an indoor corridor.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1816-1819
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• 1997

Using the vision system, robotic tasks in unstructured environments can be accompished, which reduces greatly the cost and steup time for the robotic system to fit to he well-defined and structured working environments. This paper proposes a dynamic control scheme for robot manipulator with eye-in-hand camera configuration. To perfom the tasks defined in the image plane, the camera motion Jacobian (image Jacobian) matrix is used to transform the camera motion to the objection position change. In addition, the dynamic learning controller is designed to improve the tracking performance of robotic system. the proposed control scheme is implemented for tasks of tracking moving objects and shown to outperform the conventional visual servo system in convergence and robustness to parameter uncertainty, disturbances, low sampling rate, etc.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.3
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• pp.267-272
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• 2004

In this Paper, we present analysis on the dynamics of human swing and its realization by a miniaturized humanoid robot. Since the motion of legs is the most important in the swing, the swing system can be approximated as a double pendulum. Based on Lagrangian analysis, the leg motion is designed to make the swing motion as sustained oscillation. In order to detect the peak instant of the swing and to synchronize the leg motion with the swing, we use ADXL acceleration/inclination sensor. The miniaturized humanoid in this paper has total 20 DOFs including 6 DOFs in each leg, 34cm in height, and 2kg in weight. As a result of realization of the swing by the humanoid, the sustained oscillation is verified through experiments.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.56-61
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• 2000

Majority of industrial robots are controlled by a simple independent joint control of joint actuators rather than complex controllers based on the nonlinear dynamic model of the robot manipulator. In this independent joint control scheme, the performance of actuator control is influenced significantly by the joint disturbance torques including gravity, Coriolis and centrifugal torques, which result in the trajectory tracking error in the joint control system. The control performance of a redundant manipulator under independent joint control can be improved by minimizing this joint disturbance torque in resolving the kinematic redundancy. A 3 DOF planar robot is studied as an example, and the dynamic programming method is used to find the globally optimal joint trajectory that minimize the joint disturbance torque over the entire motion. The resulting solution is compared with the solution obtained by the conventional joint torque minimization, and it is shown that joint disturbance can be reduced using the kinematic redundancy.