• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.501-506
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• 1988

This paper describes an experimental system for automatic robot programming, The SNU-ARPS (Seoul National University Automatic Robot Programming System). The SNU-ARPS generates executable robot programs for pick and place operation and some simple mechanical assembly tasks by menudriven dialog. It is intended to enable the user to concentrate on the overall operation sequence instead of the knowledge regarding the details of robot languages. To convert task specifications into manipulator motions, the SNU-ARPS uses an internal representation of the world. This representation initially consists of geometric database from CAD system and is updated at each operation step to reflect the state changes of the world.

• 수산해양기술연구
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• 제29권4호
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• pp.279-285
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• 1993

Robot inverse kinematics solution is a complex nonlinear equation and very time-consuming task. This paper propose to use TSK fuzzy reasoning for solving robot inverse kinematics. A fuzzy model of inverse kinematics is identified by using input-output data and the model is used to solve the inverse kinematics. To show that, when used in robot inverse kinematics, fuzzy model is simple and generates a fairly accurate solution, a fuzzy model of inverse kinematics for PUMA robot is constructed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.59.5-59
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• 2001

Multi-agent robot system is the system which executes by cooperating with each robots and controlling several robots. Capability and function of each robot must be considered for cooperation behavior. Furthermore, it is necessary to analyze the given environment and to replace complex task with some simple tasks. Analysis of the given environment and role assignment for the given tasks are composed of discret event. In this paper, the hierarchical controller for multi-agent robot system using the petri-net state diagram is proposed. The proposed modeling method is implemented for soccer robot system. The effectiveness of proposed modeling method is shown through experiment.

• 로봇학회논문지
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• 제16권1호
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• pp.56-63
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• 2021

As the use of robots in service area increases, research has been conducted to replace human tasks in daily life with robots. Among them, this study focuses on the tidy-up task on a desk using a robot arm. The order in which tidy-up motions are carried out has a great impact on the success rate of the task. Therefore, in this study, a neural network-based method for determining the priority of the tidy-up motions from the input image is proposed. Reinforcement learning, which shows good performance in the sequential decision-making process, is used to train such a task planner. The training process is conducted in a virtual tidy-up environment that is configured the same as the actual tidy-up environment. To transfer the learning results in the virtual environment to the actual environment, the input image is preprocessed into a segmented image. In addition, the use of a neural network that excludes unnecessary tidy-up motions from the priority during the tidy-up operation increases the success rate of the task planner. Experiments were conducted in the real world to verify the proposed task planning method.

• 컴퓨터교육학회논문지
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• 제16권4호
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• pp.13-21
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• 2013

최근 초등학생을 대상으로 다양한 교육용 프로그래밍 언어와 교수학습방법이 개발됨에 따라 교육현장에서 활발하게 프로그래밍 교육이 이루어지고 있다. 그러나 대부분의 프로그래밍 교육이 초등학교 고학년 학생을 대상으로 하고 있으며, 문제해결과정 보다 도구의 사용법에 중점을 두고 있어서 정보교육 전반에 활용되기에는 한계가 있다. 정보교육에서 프로그래밍 활동이 활발히 이루어지기 위해서는 학습대상을 넓히고 교육내용을 사고력 측면에서 고려할 필요성이 있다. 따라서 본 연구에서는 초등학교 저학년 학생도 쉽게 사용할 수 있는 프로그래밍 도구와 사고력 향상을 중심으로 하는 프로그래밍 과제를 제안하였다. 프로그래밍 도구는 텐지블 유저 인터페이스(Tangible User Interface, TUI)를 기반으로 초등학교 저학년 학생도 쉽게 사용할 수 있도록 하였으며, 프로그래밍 과제는 로봇을 활용하여 논리적 사고를 향상시키는 목적으로 개발하였다. 실험을 통해 텐지블 프로그래밍 도구가 초등학교 저학년도 쉽게 사용할 수 있는 도구적 사용성을 나타내었고, 개발한 과제 또한 논리사고력 향상에 효과가 있음을 보여주었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.111-116
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• 1998

In this study, we try to coincide virtual robot system in an OLP(off-line programming) with actual robot system even though kinematic differences between them are made. The virtual robot in the OLP may be modeled according to kinematics of the actual robot system. However, it is a complicated problem to find exactly all kinematic parameters of actual robot and environment. In this paper, an automated calibration method is proposed In order to find some kinematical parameters which are necessary for the modeling of a robot and environment in the OLP. It is applicable to SCARA robot for assembly task. In this method, a well-marked worktable of environment Is regarded as reference coordinate frame. The robot detects some marks on the worktable through sensors attached to the end-effector. The necessary parameters are calculated from the data of the robot joint variables when the robot detects the mark. The model in the OLP is modified by the parameters.

• 대한인간공학회지
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• 제11권2호
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• pp.15-21
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• 1992

This paper presents the ROBOT MODAPTS(Modular Arrangement of Predetermi- ned Time Standards) technique which can be applied to the robot motion analysis. Robot motions are easily divided into several movement activities and terminal activi- ties by means of the ROBOT MODAPTS technique Each link of robot arm is numbered such that finger is 1, hand is 2, elbow is 3, and so on. The robot motion time of each link is counted by multipling its given number to some time values observed at the finger movement. We can easily estimate robot teaching task time with this technique. This technique can be applied efficiently to establishing an adaptable robot motion ergonomically.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1039-1043
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• 2005

Despite the many significant advances made in robot architecture, the basic approaches are deliberative and reactive methods. They are quite different in recognizing outer environment and inner operating mechanism. For this reason, they have almost opposite characteristics. Later, researchers integrate these two approaches into hybrid architecture. In such architecture, Reactive module also called low-level motion control module have advantage in real-time reacting and sensing outer environment; Deliberative module also called high-level task planning module is good at planning task using world knowledge, reasoning and intelligent computing. This paper presents a framework of the integrated planning and control for mobile robot navigation. Unlike the existing hybrid architecture, it learns topological map from the world map by using MST (Minimum Spanning Tree)-based SOFM (Self-Organizing Feature Map) algorithm. High-level planning module plans simple tasks to low-level control module and low-level control module feedbacks the environment information to high-level planning module. This method allows for a tight integration between high-level and low-level modules, which provide real-time performance and strong adaptability and reactivity to outer environment and its unforeseen changes. This proposed framework is verified by simulation.

• 제어로봇시스템학회논문지
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• 제13권1호
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• pp.65-71
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• 2007

Adjustable autonomy architecture provides various ways for a human operator to participate as a member of a human-robot team in improving the performance of the team by resolving issues that the robots cannot deal with or performing tasks that the robots alone would unable to do. According to the level of involvement of the human operator, the robots have to adjust their level of autonomy and, in consequence, the operation mode of the overall system shifts. This paper deals with the implementation issues of seamless switching when the level of autonomy of the human-robot team shifts from one level to another. Especially, we focus on developing reliable methods for monitoring the task progress and maximizing the system flexibility by coping with the detailed differences between humans and robots in their characteristics of motions and their choices of positions, paths, and sequences of sub-goals to achieve a given task. To test and motivate the proposed methods, we have assembled three heterogeneous robots which work together to dock both ends of a suspended beam into stanchions.

• 한국컴퓨터정보학회논문지
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• 제15권1호
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• pp.61-69
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• 2010

로봇이 동작하는 환경을 완벽하게 커버리지 하기 위해서는 전체환경 지도를 가지고 있어야 한다. 그러나 대부분의 기존 커버리지 알고리즘은 로봇이 동작하기 전 사전에 생성된 지도가 있어야 동작 한다. 이런 이유로 기존의 커버리지 알고리즘은 미지의 환경에 바로 적용할 수 없는 문제를 가지고 있다. 미지의 환경에서 로봇이 모든 영역을 커버리지 하기위해서는 로봇스스로 환경 지도를 생성할 수 있어야한다. 본 논문에서는 SLAM 알고리즘을 통합하여 미지의 환경에서 로봇이 환경 지도를 생성하며 생성된 지도를 기반으로 커버리지를 수행하는 DmaxCoverage 알고리즘을 제안한다. 시뮬레이션 실험을 통해서 DmaxCoverage 알고리즘이 기존의 커버리지 알고리즘에 비해서 효율적임을 증명하였다.