• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.151-156
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• 2005

This paper proposes a Distributed Autonomous Robotic System(DARS) based on an Artificial Immune System(AIS) and a Classifier System(CS). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in given environment. These actions are composed of two types: aggregation and dispersion. AIS decides one among these two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the CS in the local one. The proposed system will be more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.493-498
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• 2011

This paper presents the GraphSLAM improved by selecting the measurement with respect to their likelihoods. GraphSLAM estimates the robot's path and map by utilizing the entire history of input data. However, GraphSLAM's performance suffers a lot from severely noisy measurements. In this paper, we present GraphSLAM improved by the selective measurement method. Thus the presented GraphSLAM provides higher performance compared with the standard GraphSLAM.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.43-45
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• 2008

위 인식은 이동 로봇의 자율 주행을 위한 필수 기능이다. 위치 추정을 위해서 Bayes Filter를 기본으로한 칼만 필터 방법들이 주로 제안되어졌고 최근에는 Particle Filter 방법이 제안되어져 사용되고 있다. 본 연구에서는 영역센서를 장착한 이동 로봇의 위치 추정을 위해 레이저 영역 센서를 이용하는 Particle Filter 방법을 구현하였다. Particle Filter방법은 Kalman Filter 방법에 비해서 구현이 간단하면서도 Kidnapping 문제에도 대응할 수 있는 장점이 있다. 본 연구를 통하여 위치 추정의 수렴도, 정확도, 그리고 Kidnapping 발생시의 위치 추정 성능등을 분석하여, 기존 방법의 성능을 개선하는 방법을 제안한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.143-146
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• 2008

본 논문에서는 군집로봇시스템에서 목표물 추적을 위하여 SVM을 이용한 12각형 기반의 Q-learning 알고리즘을 제안한다. 제안한 알고리즘의 유효성을 보이기 위해 본 논문에서는 여러대의 로봇과 장애물 그리고 하나의 목표물을 정하고, 각각의 로봇이 숨겨진 목표물을 찾아내는 실험을 가정하여 무작위, DBAM과 ABAM의 융합 모델, 그리고 마지막으로 본 논문에서 제안한 SVM과 12각형 기반의 Q-learning 알고리즘을 이용하여 실험을 수행하고, 이 3가지 방법을 비교하여 본 논문의 유효성을 검증하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.400-402
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• 2008

The human-computer interaction technology (HCI) that has played an important role in the exchange of information between human being and computer belongs to a key field for information technology. Recently, control studies through which robots and control devices are controlled by using the movements of a person's body or hands without using conventional input devices such as keyboard and mouse, have been going only in diverse aspects, and their importance has been steadily increasing. This study is proposing a recognition method of user's gestures by applying measurements from an acceleration sensor to the PCA algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.274-274
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• 2000

In the future, the convenient speech command system will become an widely-using interface in automation systems. But the previous research in speech recognition didn't give satisfactory recognition results for the practical realization in the noise environment. The purpose of this research is the development of a practical system, which reliably recognizes the speech command of the registered users, by complementing an existing research which used the image information with the speech signal. For the lip-reading feature extraction from a image, we used the DWT(Discrete Wavelet Transform), which reduces the size and gives useful characteristics of the original image. And to enhance the robustness to the environmental changes of speakers, we acquired the speech signal by stereo method. We designed an economic stand-alone system, which adopted a Bt829 and an AD1819B with a TMS320C31 DSP based add-on board.

• Journal of Korea Society of Industrial Information Systems
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• v.1 no.1
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• pp.153-176
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• 1996

The new field of learning control devleops controllers that learn to improve their performance at executing a given task, based on experience performing this task. the simplest forms of learning control are based on the same concepts as integral control, but operating in the domain of the repetitions of the task. This paper studies the use of such controllers ina decentralized system, such as a robot with the controller for each link acting independently. The basic result of the paper is to show that stability of the learning controllers for all subsystems when the coupling between subsystems is turned off, assures stability of the decentralized learning in the coupled system, provided that the sample time in the digital learning controller is sufficiently short.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.263-266
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• 1997

로봇 축구 경기를 위해서는 경기장의 임의의 시작점에서 목표점으로 장애물을 피해 갈 수 있는 능력이 필요하다. 이러한 경로 계획을 학습하기 위해서 다양한 상황을 모두 고려할 경우 학습량이 급격히 증가한다. 그러나 많은 실제적인 학습 문제에 있어서는 가능한 모든 학습 데이터를 사용하지 않고도 원하는 학습 효과를 가져올 수 있음이 알려져 있으며, 이러한 경우 데이터를 스스로 선별하여 학습하는 능동적 학습 방법이 효과적이다. 본 논문에서는 진화 알고리즘을 사용하여 실시간에 경로 계획을 하기 위한 새로운 능동적 학습 방법을 제시한다. 제안되는 방법은 두 개의 진화 알고리즘으로 구성되는데 하나는 주어진 시작점-목표점간의 최적 경로를 찾는데 사용되고 또 다른 하나의 진화 알고리즘은 유용한 시작점-목표점들의 쌍을 탐색하는데 사용된다. 이 방법은 계산 시간의 여유가 있을 때 다양한 문제를 스스로 제시하고 해결하는 법을 학습해 놓고 후에 실제 문제가 주어질 때 기존의 문제와 가장 유사한 문제를 찾아 실시간에 해결함으로써 기존의 진화 알고리즘에 의한 경로 계획법들이 갖는 실시간성에서의 단점을 개선할 수 있다. 실험을 통하\ulcorner 제안된 두 가지 진화 알고리즘의 성능을 실험적으로 검토한다.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.593-598
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• 2014

Hand gesture recognition based on vision is a challenging task in human-robot interaction. The sign language of finger spelling alphabets has been tested as a kind of hand gesture. In this paper, we test hand gesture recognition by detecting the contour shape and orientation of hand with visual image. The method has three stages, the first stage of finding hand component separated from the background image, the second stage of extracting the contour feature over the hand component and the last stage of comparing the feature with the reference features in the database. Here, finger spelling alphabets are used to verify the performance of our system and our method shows good performance to discriminate finger alphabets.