• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.128-130
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• 1997

In the paper a problem of search for a moving robot by another moving robot is considered. The problem is formalized as minmax and maxmin task also as a game.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.62-66
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the learning control field was learning in robots doing repetitive tasks such as an assembly line works. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown for the iterative precision of each link.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.92-98
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• 2005

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized teaming control based on adaptive control method. The original motivation of the teaming control field was loaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.445-452
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• 2012

With the increasing number of high-rise and large-scale buildings, modern buildings are becoming intelligent, and are incurring high construction costs and requiring careful maintenance. Maintenance works for high-rise buildings significantly depend on human labor, unlike other construction processes that are gradually being automated. The resulting accidents may produce very high social and economic losses. To address this problem, herein, this paper proposes robotic building maintenance system using multi-robot concept, in specific, cleaning a building facade which is directly subjected to minimize human labor; that improves the process efficiency and economic feasibility. The sensor for detecting contamination of building's outer-wall glass is proposed; Kalman filter was used for estimating robots' status with the contamination of the window glass. Task allocation of the sensor based multi-robots for an effective way of task execution is introduced and the feasibility was verified through the simulations.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.119-126
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• 2002

In this paper, we present a new approach based on an elitist genetic algorithm for the task of aligning the position of a robot gripper using CCD cameras. The vision-based control scheme for the task of aligning the gripper with the desired position is implemented by image information. The relationship between the camera space location and the robot joint coordinates is estimated using a camera-space parameter modal that generalizes known manipulator kinematics to accommodate unknown relative camera position and orientation. To find the joint angles of a robot manipulator for reaching the target position in the image space, we apply an elitist genetic algorithm instead of a nonlinear least square error method. Since GA employs parallel search, it has good performance in solving optimization problems. In order to improve convergence speed, the real coding method and geometry constraint conditions are used. Experiments are carried out to exhibit the effectiveness of vision-based control using an elitist genetic algorithm with a real coding method.

• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.270-276
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• 2016

This paper proposes a design methodology of self-reconfigurable kinematics and control engine for modular and reconfigurable robots. A modular manipulator has been proposed to meet the requirement of task adaptation in versatile needs for service and industrial robot area and the function of self-reconfiguration is required to extend the application of modular robots. Kinematic and dynamic contexts are extracted from the module and assembly information and related codes are automatically generated including controller. Thus a user can easily build and use a modular robot without professional knowledge. Simulation results are presented to verify the validity of the proposed method.

• The Journal of Korea Robotics Society
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• v.12 no.1
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• pp.42-54
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• 2017

Using an inverse of the geometric Jacobian matrix is one of the most popular ways to control robot manipulators, because the Jacobian matrix contains the relationship between joint space velocities and operational space velocities. However, the control algorithm based on Jacobian matrix has algorithmic singularities: The robot manipulator becomes unstable when the Jacobian matrix loses rank. To solve this problem, various methods such as damped and filtered inverse have been proposed, but comparative studies to evaluate the performance of these algorithms are insufficient. Thus, this paper deals with a comparative analysis of six representative singularity avoidance algorithms: Damped Pseudo Inverse, Error Damped Pseudo Inverse, Scaled Jacobian Transpose, Selectively Damped Inverse, Filtered Inverse, and Task Transition Method. Especially, these algorithms are verified through computer simulations with a virtual model of a humanoid robot, THORMANG, in order to evaluate tracking error, computational time, and multiple task performance. With the experimental results, this paper contains a deep discussion about the effectiveness and limitations of each algorithm.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.2
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• pp.430-440
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• 2015

The purpose of this study was to analyze student's metacognition interaction based on a robot lesson. For this research as an analytical metacognition interaction tool was utilized. The results of this study revealed that, first, elementary school students had more metacognition interaction in middle learning levels but middle school students had more in the low learning level. Second, in the low learning level, middle school students revised the initiated goal strategy of the robot lesson. Third, in all learning levels, students showed much diagnosis and assesment metacognition interaction in the robot lesson. According to this study's results, the robot lesson has a positive effect in facilitating diagnosis meta cognition for processing of task performance. These results could provide effective cues and information on how to improve the robot lesson.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.681-690
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• 2007

This article presents the kinematic analysis and implementation of an interface and control of two robots-an exoskeleton master robot and a human-like slave robot with two arms. Two robots are designed and built to be used for motion-following tasks. The operator wears the exoskeleton master robot to generate motions, and the slave robot is required to follow after the motion of the master robot. To synchronize the motions of two robots, kinematic analysis is performed to correct the kinematic mismatch between two robots. Hardware implementation of interface and control is done to test motion-following tasks. Experiments are performed to confirm the feasibility of the motion-following tasks by two robots.