• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권3호
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• pp.220-224
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• 2008

This paper presents the polygon-based Q-leaning and Parallel SVM algorithm for object search with multiple robots. We organized an experimental environment with one hundred mobile robots, two hundred obstacles, and ten objects. Then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning, and dodecagon-based Q-learning and parallel SVM algorithm to enhance the fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process. In this paper, the result show that dodecagon-based Q-learning and parallel SVM algorithm is better than the other algorithm to tracking for object.

• 한국지능시스템학회논문지
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• 제16권3호
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• pp.275-284
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• 2006

본 논문에서는 자율이동로봇이 주위 환경을 알지 못하는 상황에서 목표점까지 안전하게 주행하게 하는 주행 알고리즘에 대해 연구한다. 주행 알고리즘에서 가장 고려해야할 부분이 장애물 회피 알고리즘인데, 본 논문에서는 장애물 회피 알고리즘인 VFH(Vector Field Histogram) 알고리즘과 퍼지 알고리즘을 조합하여 여러 가지 형태의 환경에서 최적의 성능을 내도록 한다. 로봇이 처한 환경에 따라 상위 레벨의 supervisor가 위의 두 가지 장애물 회피 알고리즘 중 적절한 것을 선택하도록 조합하고, 다양한 환경에서 모의실험을 수행함으로써 제안된 로봇주행 알고리즘의 성능을 검증한다.

• 한국지능시스템학회논문지
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• 제15권4호
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• pp.498-504
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• 2005

본 논문에서는 퍼지 로직을 이용한 수중 로봇의 충돌 회피를 제안하였다. VFF(Virtual Force Field) 방법은 이동 로봇 분야에서 널리 사용하고 있는 충돌 회피 알고리즘이다. 본 논문에서는 이를 수중 로봇의 자율 항해를 위한 형태로 변형시킨 Modified Virtual Force Field(MVFF)를 제시하였다. 보다 정교한 알고리즘을 위해서 퍼지 로직을 이용한 MVFF를 구성하였고, 이를 수중 로봇의 경로 유지와 충돌 회피에 적용하였다 퍼지 로직은 수중 로봇의 자율 항해 동안 직면하게 되는 다양한 상황들을 다루었다. 제안한 충돌 회피 알고리즘은 다수개의 고정 장애물에 대해서 좋은 성능을 제시하였다. 시뮬레이션 결과를 통해 제안된 방법이 수중 로봇의 충돌 회피에 효과적으로 적용될 수 있음을 보였다.

• 한국지능시스템학회논문지
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• 제21권6호
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• pp.673-678
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• 2011

본 논문에서는 물체의이동이나 정보 탐색을위하여 유용하게 사용될 수 있는 4족 로봇의 정지 밸런스를 분석하고자 한다. 이 목적을위하여, 일반적인 4족 로봇의유용한 모델을 제시하고, 정지 안정성을 고려한 경계 조건을 제안한다. 착지된 상태에서 4족 로봇의 정지 밸런스를 분석하기 위하여 다양한 자유 운동을 고려하며, 시뮬레이션을 통하여 밸런스 여유를 고찰한다. 이러한 분석은 4족 로봇 보행의 효과적인 밸런싱 제어를 위하여 유용하게 활용될 수 있을것이다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2568-2574
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• 2005

Control architecture of the action based robot engineering can be divided into two types of deliberate type - and reactive type- controller. Typical deliberate type, slow in reaction speed, is well suited for the realization of the higher intelligence with its capability to forecast on the basis of environmental model according to time flow, while reactive type is suitable for the lower intelligence as it fits to the realization of speedy reactive action by inputting the sensor without a complete environmental model. Looking at the environments in the application areas in which robots are actually used, we can see that they have been mostly covered by the uncertain and unknown dynamic changes depending on time and place, the previously known knowledge being existed though. It may cause, therefore, any deterioration of the robot performance as well as further happen such cases as the robots can not carry out their desired performances, when any one of these two types is solely engaged. Accordingly this paper aims at suggesting Goal-oriented Geometric Model(GGM) Based Intelligent System Architecture which leads the actions of the robots to perform their jobs under variously changing environment and applying the suggested system structure to the navigation issues of the robots. When the robots do perform navigation in human life changing in a various manner with time, they can appropriately respond to the changing environment by doing the action with the recognition of the state. Extending this concept to cover the highest hierarchy without sticking only to the actions of the robots can lead us to apply to the algorithm to perform various small jobs required for the carrying-out of a large main job.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.504-510
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• 1998

In this paper, Fundamental rules governing group intelligence "obstacle avoidance" behavior of multiple autonomous mobile robots are represented by a small number of fuzzy rules. Complex lifelike behavior is considered as local interactions between simple individuals under small number of fundamental rules. The fuzzy rules for obstacle avoidance are generated from clustering the input-output data obtained from the obstacle avoidance algorithm. Simulation shows the fuzzy rules successfully realizes fundamental rules of the obstacle avoidance behavior.

• 로봇학회논문지
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• 제4권1호
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• pp.49-55
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• 2009

The development of IT technology makes the functions and services of robots be integrated, and thus the robots become more intelligent and useful. As sophisticated usage of robots has evolved, direct communication by human language is necessary to increase the efficiency of their usage. In this paper, we propose a conversational interface platform for integrated service robots using MS Robotics Studio. The proposed platform consists of three types of components: a conversation manager to control the flows of the integrated service robots, a user interface to interact with users, and multiple service robots to perform actions or services. For a test-bed of the proposed platform, we build a schedule manager system and confirm the usability through SUS subject test by comparing the schedule manager system with MS Outlook.

• 제어로봇시스템학회논문지
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• 제10권9호
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• pp.771-778
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• 2004

Recently, various applications of robot system become more popular in accordance with rapid development of computer hardware/software, artificial intelligence, and automatic control technology. Formerly robots mainly have been used in industrial field, however, nowadays it is said that the robot will do an important role in the home service application. To make the robot more useful, we require further researches on implementation of natural communication method between the human and the robot system, and autonomous behavior generation. The gesture recognition technique is one of the most convenient methods for natural human-robot interaction, so it is to be solved for implementation of intelligent robot system. In this paper, we describe the state-of-the-art of advanced gesture recognition technologies for intelligent robots according to three methods; sensor based method, feature based method, appearance based method, and 3D model based method. And we also discuss some problems and real applications in the research field.

• 한국지능시스템학회논문지
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• 제19권4호
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• pp.470-477
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• 2009

자기 자신의 형태를 변형하거나 물리적인 결합으로 재구성하여 새로운 환경에 적응하는 모듈형 자가 결합 로봇은 많은 연구가 필요한 분야이다. 본 논문에서는 물리적으로 결합 가능한 모듈형 로봇을 위한 영상기반의 자가 결합 제어기를 제안한다. 먼저 실시간 영상처리가 가능한 모듈형 로봇 플랫폼을 설계하고, 컬러기반 물체 인식 방법을 구현하였다. 모듈형 로봇은 자가 결합을 위해 결합될 로봇 근처의 부목표점까지 장애물들을 회피하면서 주행해 가야 한다. 본 논문에서는 부 목표점의 추적을 위하여 영상처리를 통해 얻은 거리와 방향각 정보들을 사용한 퍼지 주행 제어기와 장애물 회피를 위한 퍼지 제어기를 제안하고, 제안된 퍼지 제어기들과 로봇의 절대 거리 및 방향각 정보를 사용하여 모듈형 로봇을 위한 자가 결합제어기를 구현하였다. 실제 제작된 두 대의 모듈형 로봇을 사용하여 다양한 환경에서 로봇간 거리와 방향각이 다른 상황에서 실험을 수행하여 제안된 자가 결합 제어 방법의 성능을 검증하였다.

• International Journal of Control, Automation, and Systems
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• 제6권2호
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• pp.282-287
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• 2008

In distributed mobile robot systems, autonomous robots accomplish complicated tasks through intelligent cooperation with each other. This paper presents behavior learning and online distributed evolution for cooperative behavior of a group of autonomous robots. Learning and evolution capabilities are essential for a group of autonomous robots to adapt to unstructured environments. Behavior learning finds an optimal state-action mapping of a robot for a given operating condition. In behavior learning, a Q-learning algorithm is modified to handle delayed rewards in the distributed robot systems. A group of robots implements cooperative behaviors through communication with other robots. Individual robots improve the state-action mapping through online evolution with the crossover operator based on the Q-values and their update frequencies. A cooperative material search problem demonstrated the effectiveness of the proposed behavior learning and online distributed evolution method for implementing cooperative behavior of a group of autonomous mobile robots.