• Proceedings of the KSME Conference
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• 2003.04a
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• pp.758-763
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• 2003

This paper describes the development of a 6-axis robot's finger force/moment sensor, which measures forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously, for making a robot's gripper. In order to safely grasp and unknown object using the robot's gripper, it should measure the force in the gripping direction and the force in the gravity direction, and perform the force control using the measured forces. Thus, the robot's gripper should be composed of 6-axis robot's finger force/moment sensor that can measure forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously. In this paper, the 6-axis robot's finger force/moment sensor for measuring forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously was newly modeled using several parallel-plate beams, designed, and fabricated. The characteristic test of made sensor was performed. Also, Robot's gripper with the 6-axis robot's finger force/moment sensor for the characteristic test of force control was manufactured, and the characteristic test for grasping an unknown object was performed using it.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.227-230
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• 1997

In this paper, robot navigation experiments with a new navigation algorithm are carried out in real environments. The authors already proposed a reactive navigation algorithm for mobile robots using optimal via-point selection method. At each sampling time, a number of via-point candidates is constructed with various candidates of heading angles and velocities. The robot detects surrounding obstacles, and the proposed algorithm utilizes fuzzy multi-attribute decision making in selecting the optimal via-point the robot would proceed at next step. Fuzzy decision making allows the robot to choose the most qualified via-point even when the two navigation goals-obstacle avoidance and target point reaching-conflict each other. The experimental result shows the successful navigation can be achieved with the proposed navigation algorithm for real environments.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.49.1-49
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• 2002

$\textbullet$ Intelligent Space 1. Optimal Camera Arrangement 2. People Tracking 3. Physical Robot 4. Robot Control 5. People Following Robot $\textbullet$ Initial stage for making high-level human robot interaction. http://dfs.iis.u-tokyo.ac.jp/∼leejooho/ispace/.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.282-287
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• 2007

Humanoid and android robots are emerging as a trend shifts from industrial robot to personal robot. So human-robot interaction will increase. Ultimate objective of humanoid and android would be a robot like a human. In this aspect, implementation of robot's facial expression is necessary in making a human-like robot. This paper proposes a dynamic emotion model for a mascot-type robot to display similar facial and more recognizable expressions.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1161-1164
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• 1996

In this paper, a parameter optimization technique for a mobile robot navigation is discussed. Authors already have proposed a navigation algorithm for mobile robots with sonar sensors using fuzzy decision making theory. Fuzzy decision making selects the optimal via-point utilizing membership values of each via-point candidate for fuzzy navigation goals. However, to make a robot successfully navigate through an unknown and cluttered environment, one needs to adjust parameters of membership function, thus changing shape of MF, for each fuzzy goal. Furthermore, the change in robot configuration, like change in sensor arrangement or sensing range, invokes another adjusting of MFs. To accomplish an intelligent way to adjust these parameters, we adopted a genetic algorithm, which does not require any formulation of the problem, thus more appropriate for robot navigation. Genetic algorithm generates the fittest parameter set through crossover and mutation operation of its string representation. The fitness of a parameter set is assigned after a simulation run according to its time of travel, accumulated heading angle change and collision. A series of simulations for several different environments is carried out to verify the proposed method. The results show the optimal parameters can be acquired with this method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.491-495
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• 1993

In this paper, we present a methodology to model an indoor environment of a mobile robot using fuzzy numbers and to make a global map of the robot environment using graph theory. We describe any geometric primitive of robot environment as a parameter vector in parameter space and represent the ill-known values of the prameterized geometric primitive by means of fuzzy numbers restricted to appropriate membership functions. Also we describe the spatial relations between geometric prinitives using graph theory for local maps. For making the global map of the mobile robot environment, the correspondence problem between local maps is solved using a fuzzy similarity measure and a Bipartite graph matching technique.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.530-532
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• 2006

In this paper, we propose stable walking algorithm using ZMP for the biped robot in the slope-way. At first, we define discrete state variables that classified stable area and unstable area by center of mass from ZMP during slope-way walking. For the stable walking gait, the discrete state controller for determining the high-level and low-level decision making are designed. The high-level decision making is composed of the discrete state variables; left foot support phase, right foot support phase, flat-way, and slope-way. Then the continuous state controller is implemented for the low-level decision making using ZMP.

• 대한공업교육학회지
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• v.34 no.1
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• pp.210-237
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• 2009

The aim of this thesis is to develop a robot C programming curriculum with the subject of the students in the middle & High School and to prove the effect of the programming on creativity and programming ability. The content of the robot C programming curriculum consists of the introduction, basic knowledge and assembling of the robot (usage of kits and the theory of mechanism); the learning of the robot c programming; the assigned robot making; the original robot making, which is ultimately designed to improve the creative robot programming ability of students. The subjects are divided into two groups(38); one groups(11) taking the course of C++programming and the other(27) taking the robot C programming as well as C++programming. Then each group's improvement of creativity and programming ability is measured in both pretest and posttest. The students taking the robot C programming curriculum gain the product of the assigned robot and the original robot. Besides, it turns out that the curriculum have a meaningful effect in that students acquire the enhanced creativity according to the result of TTCT Creativity Test. Self evaluation also indicates the improvement of C++programming ability.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.124-127
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• 1997

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is simulated and suppressed by other robot using communication. Finally much simulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.635-641
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• 2008

In this paper, we used a laser range finder (LRF) to detect both the static and dynamic obstacles for the safe navigation of a mobile robot. LRF sensor measurements containing the information of obstacle's geometry are first processed to extract the characteristic points of the obstacle in the sensor field of view. Then the dynamic states of the characteristic points are approximated using kinematic model, which are tracked by associating the measurements with Probability Data Association Filter. Finally, the collision avoidance algorithm is developed by using fuzzy decision making algorithm depending on the states of the obstacles tracked by the proposed obstacle tracking algorithm. The performance of the proposed algorithm is evaluated through experiments with the experimental mobile robot.