• The Journal of Korea Robotics Society
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• v.5 no.4
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• pp.318-325
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• 2010

This paper proposes a new string controller for puppet which is optimized in terms of the number of motors and its size. To optimize the number of motors needed for generating the essential motions of puppet, the motion of bending a leg is implemented by one string and the walking motion by two legs is implemented by one motor. To minimize the space needed for the controller when generating the essential motions of puppet, cylindrical and articulated joints are used in the controller. The proposed controller is actually implemented to perform various puppet shows and it has been proved that the size of the controller is small enough for two puppets to stand close to shake hands and it is fast enough to simulate fast dance motions.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.299-301
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• 1996

Since a standard lens has small sight angle, a fish-eye lens can be used in order to obtain wide sight angle for the robot vision system. In spite of the advantage, the image through the lens has variable resolution; the central information of the lens is of high resolution, but the peripheral information is of low resolution. Owing to this difference of resolution, the variable resolution image should be transformed to a uniform resolution image in order to determine the positions of the objects in the image. In this work, the correction method for the distorted image is presented and the performance is analyzed. Furthermore, the camera with a fish eye lens can be used to determine the real world coordinates. The performance is shown through experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1044-1047
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• 2005

In this paper, we present the strategy of object search for distributed autonomous robotic systems (DARS). The DARS are the systems that consist of multiple autonomous robotic agents to whom required functions are distributed. For instance, the agents should recognize their surrounding at where they are located and generate some rules to act upon by themselves. In this paper, we introduce the strategy for multiple DARS robots to search a hidden object at the unknown area. First, we present an area-based action making process to determine the direction change of the robots during their maneuvers. Second, we also present Q learning adaptation to enhance the area-based action making process. Third, we introduce the coordinate system to represent a robot's current location. In the end of this paper, we show experimental results using hexagon-based Q learning to find the hidden object.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1922-1927
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• 2005

This paper describes the mechanism of a new biped machine capable of doing human-robot cooperation work. The biped machine, WABIAN-2 is made of two seven degrees of freedom (DOF) legs, a two DOF waist and no DOF trunk. Its leg system consists of two three DOF ankles, two one DOF knees and two three DOF hips to deal with various walk motions. Its height is about 1.2[m], and its weight is 40[kg]. It is designed with large movable range as a human. Also, a knee stretch walk pattern generation for the biped machine to perform natural walk like a human is discussed in this paper. Its leg motion is compensated by using the motion of its waist. Basic knee stretch walk experiments using WABIAN-2 are conducted on the plane, and the validity of its mechanism and walk pattern generator is verified.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.780-783
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• 2007

A Many studies have been made on the prediction of human voluntary movement intention in real-time based on invasive or non-invasive methods to help severely motor-disabled persons by offering some abilities of motor controls and communications. In the present study, we have developed an internet game driven by and/or linked to a brain-computer interface (BCI) system. Activities of two single neuronal units recorded from either hippocampus or prefrontal cortex of SD rats were used in real time to control two-dimensional movements of a robot, or a game object.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.56-59
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• 2004

GPS(global position system)은 특별한 표식이 없는 외부환경에서 위치 측정을 위한 가장 좋은 가능성을 보여주고 있다 그러나 현재 GPS의 오차에 의해서 위치 측정은 불가능하다. 또한 속도가 느린 이동로봇의 방향정보를 얻는 것도 힘들다. 본 논문에서는 지자기 센서를 이용하여 이동로봇의 방향정보를 이용하고 이동로봇의 인코더와 GPS를 이용하여 보다 정밀한 위치 측정이 가능하게 하였다. 이를 바탕으로 이동로봇의 지도를 작성하고 이동로봇의 안전한 경로를 신경망을 이용하여 학습하여 고장이나 충돌회피에 의해 이동로봇이 위험한 경로로 이동하는 것을 사전에 방지하였다. 또한 지도와 획득한 위치정보를 바탕으로 특정위치에서 임무를 수행함으로써 이동로봇이 외부환경에서의 방범활동이나 산업현장에 적용될 수 있음을 보이고자 한다.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.890-893
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• 1999

The intent of this paper is to describe a neural network structure called dynamic neural processor(DNP), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. Computer simulations are demonstrate the effectiveness of the Proposed learning using the DNP.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.100.3-100
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• 2002

This paper presents the method for detection and tracking of multiple humans robustly in mobile platform. The perception of human is performed in real time through the processing of images acquired from a moving stereo vision system. We performed multi-cue integration such as human shape, skin color and depth information to detect and track each human in moving background scene. Human shape is measured by edge-based template matching on distance transformed image. Improving robustness for human detection, we apply the human face skin color in HSV color space. And we could increase the accuracy and the robustness in both detection and tracking by applying random sampling stochastic estimati...

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1733-1734
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• 2008

We develope a riding robot system named as "RideBot" for health-care and entertainments. An algorithm for estimating riding position and volition is proposed by using bio-signals. We analyze the riding position and volition in real-horse riding environments and build up the database. With this database and sensor informations, standard positions are made. For the volition estimation, we use the acceleration and deceleration sensor information and bridle information for direction change. We propose a hybrid control algorithm in which discrete-state and continuous-state controls are combined. The efficiency of the proposed algorithm is evaluated thru various experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.3
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• pp.3-11
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• 1997

One of major research areas in the recurrent neural network is to develop stable learning algorithm. In this paper, the stable learning algorithm is developed by utilizing the evolutionary programming. The effectiveness of the proposed learning algorithm will be verified by simulating two d.0.f. robot manipulator.