• 정보처리학회논문지A
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• 제18A권5호
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• pp.165-176
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• 2011

본 논문에서는 대학생 대상의 ROBOTC 기반 레고 마인드스톰 NXT 로봇을 이용한 교육과정 개발 내용을 보이고, 이 과정에 대한 교육효과를 분석하였다. 교육과정은 로봇의 기본 이해와 실습, 응용로봇 실습, 창의로봇 설계 및 구현으로 구성하였다. 2009년부터 3년간 교육을 진행하는 동안, 6개 분반 총 94명의 수강생을 대상으로 설문조사를 실시하여 교육효과를 분석하였다. 분석 결과를 통해 레고 마인드스톰 NXT 로봇을 이용한 교육과정이 학습동기와 학습의욕을 불러 일으켰고, 학생들의 교과목 교육목표 및 학습성과 달성도가 우수하였음을 보인다. 또한 학생들의 수업 및 과제물 수행에 대한 참여도가 매우 높았으며, 문제해결능력과 창의력 향상에 도움을 주었고, 조별 프로젝트 수행으로 협동심도 향상되었다. 마지막으로 ROBOTC기반 프로그래밍에 의한 로봇 제어 실습으로 C언어 프로그래밍 능력 향상에도 도움을 준 것으로 나타났다.

• 로봇학회논문지
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• 제17권4호
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• pp.463-476
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• 2022

In this paper, we propose a table tennis posture classification system using a cooperative robot to develop a table tennis robot that can be trained like a real game. The most ideal table tennis robot would be a robot with a high joint driving speed and a high degree of freedom. Therefore, in this paper, we intend to use a cooperative robot with sufficient degrees of freedom to develop a robot that can be trained like a real game. However, cooperative robots have the disadvantage of slow joint driving speed. These shortcomings are expected to be overcome through quick recognition. Therefore, in this paper, we try to quickly classify the opponent's posture to overcome the slow joint driving speed. To this end, learning about dynamic postures was conducted using image data as input, and finally, three classification models were created and comparative experiments and evaluations were performed on the designated dynamic postures. In conclusion, comparative experimental data demonstrate the highest classification accuracy and fastest classification speed in classification models using MLP (Multi-Layer Perceptron), and thus demonstrate the validity of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.608-611
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• 1997

The soccer robot system consists of multi agents, with highly coordinated operation and movements so as to fulfill specific objectives, even under adverse situation. The coordination of the multi-agents is associated with a lot of supplementary work in advance. The associated issues are the position correction, prevention of communication congestion, local information sensing in addition to the need for imitating the human-like decision making. A control structure for soccer robot is designed and several behaviors and actions for a soccer robot are proposed. Variable zone defense as a basic strategy and several special strategies for fouls are applied to SOTY2 team.

• 제어로봇시스템학회논문지
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• 제5권1호
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• pp.105-114
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• 1999

By using the conceptual impedance and the elasticity of a serial chain of spring-damper system, a real-time collision-free trajectory generation algorithm is proposed. The reference points on a trajectory connected by the spring-damper system have a mechanism for self-Position adjustment to avoid a collision by the impedance, and the local adjustment of each reference point is propagated through the elasticity to a real robot at the end of the spring-damper system. As a result, the overall trajectory consisting of the reference points becomes free of collision with environmental obstacles and efficient having the shortest distance as possible. In this process, the reference points connected by the spring-damper system take role of virtual robot as global guidance for a real robot, and a cooperative optimization is carried out by the system of virtual robots. A control algorithm is proposed to implement the impedance for a car-like mobile robot.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2705-2708
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• 2003

In this paper, we propose a method that applies matrix decomposition technique to the connection of actuator capabilities of each robot to object acceleration limits for multiple cooperative robot systems. The robot systems under consideration are composed of several robot manipulators and each robot contacts a single object to carry the object while satisfying the constraints described in kinematics as well as dynamics. By manipulating kinematic and dynamic equations of both robots and objects, we at first derive a matrix relating joint torques with object acceleration, manipulate the null space of the matrix, and then we decompose the matrix into three parts representing indeterminancy, connectivity, and redundancy. With the decomposed matrix we derive the boundaries of object accelerations from given joint actuators. To show the validity of the proposed method some examples are given in which the results can be expected by intuitive observation.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.170-175
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• 1998

Transporting a large table using multiple robotic agents requires at least two group behaviors of homing and herding which are to bo coordinated in a proper sequence. Existing GP methods for multi-agent learning are not practical enough to find an optimal solution in this domain. To evolve this kind of complex cooperative behavior we use a novel method called fitness switching. This method maintains a pool of basis fitness functions each of which corresponds to a primitive group behavior. The basis functions are then progressively combined into more complex fitness functions to co-evolve more complex behavior. The performance of the presented method is compared with that of two conventional methods. Experimental results show that coevolutionary fitness switching provides an effective mechanism for evolving complex emergent behavior which may not be solved by simple genetic programming.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.809-811
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• 2000

협조행동이 요구되는 다수의 자율이동로봇 시스템에서 각 개체는 주변환경의 인식뿐만 아니라 지속적인 환경변화에 적응할 수 있는 고도의 추론능력을 요구하고 있다. 이에 본 논문에서는 강화학습을 이용하여 동적으로 변화하는 환경에서 스스로 학습하여 대처할 수 있는 협조행동 방법을 제시하였다. 강화학습은 동물의 학습방법 연구에서 비롯되었으며, 주어진 목표를 수행하는 과정에서 개체의 행동이 목표를 성취하도록 하였을 때는 그 행동에 보상을 주어 환경의 상태에 따른 최적의 행동방법을 찾아내도록 학습하는 방법이다. 따라서 본 논문에서는 포식자들이 협조행동을 통하여 능동적으로 움직이는 먹이를 잡는 까다로운 문제에 제안한 방법을 적용하여 그 성능을 검증하였다.

• 제어로봇시스템학회논문지
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• 제17권2호
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• pp.102-107
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• 2011

In this paper we present cooperation of heterogeneous robot team, composed of a wheeled robot and a helicopter for localization and map building. This heterogeneous robot team can successfully fulfill task by combining the abilities of both robots than single robot because wheeled robot and helicopter have complementing ability. The scenario describes a tightly cooperative task, where the wheeled robot move carrying the helicopter and detect obstacles, if there are obstacles, helicopter take off for map building and land, then robot team move destination avoiding obstacles. We present PID controller for position control of helicopter and transformation algorithm to global coordinate from image pixel coordinate. Experimental result show that the proposed method is valid.

• 제어로봇시스템학회논문지
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• 제11권4호
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• pp.322-329
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• 2005

This paper considers the application of mobile robot to the herding problem. The herding problem involves a ‘pursuer’ trying to herd a moving ‘evader’ to a predefined location. In this paper, two mobile robots act as pursuer and evader in the fenced area, where the pursuer robot uses a fuzzy cooperative decision strategy (FCDS) in the herding algorithm. To herd evader robot to a predefined position, the pursuer robot calculates strategic herding point and then navigates to that point using FCDS. FCDS consists of a two-level hierarchy: low level motion descriptors and a high level coordinator. In order to optimize the FCDS, we use the multi­thread evolutionary programming algorithm. The proposed algorithm is implemented in the real mobile robot system and its performance is demonstrated using experimental results.