• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.80-85
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• 2009

The performance of the robot is very limited in the conventional model-based control methods when the environments around a robot are not structured or are varying dynamically. The reason for that is the methods are based on the model of the environments which is very difficult to match with the real environments and on a path planning which is complex and time-consuming. On the other hand, the behavior-based control methods are not dependant on the model of the environments nor a complex planning. In those methods, a specific behavior is coupled with a specific sensor output, so the response of a robot is quite reactive and timely in dynamic and unstructured environments. In this thesis, we propose a situation dependant behavior based control architecture, in which a robot may behave differently to the same sensor output depending on various situations. We also show some experimental results to show the feasibility of the proposed control architecture.

• The Journal of the Korea Contents Association
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• v.19 no.11
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• pp.507-515
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• 2019

The positive effects of 'robot actor' born in the age of artificial intelligence on the characteristics of theater (comprehensive, liveness, duality, planning) is due to the collaboration with 'robot' engineers, which increases the comprehensive. It is possible to respond to it, so that various reaction are maintained in every performance, and enhanced illusion can be provided in 'robot' material works in which 'robot actor' plays the role of 'robot'. However, the power focused on the director can reduce the comprehensiceness, the synthesis is reduced, and the 'robot actor' cannot perform the sweat or breath of 'human actor'. In itself, duality is incomplete. In addition, there is a high risk that the improvisation within the scope of planning is likely to occur as a sudden reaction, which may limit the postponement of the 'human actor'. Based on these findings, 'philosophy', 'science' and 'art' can predict the development of artificial intelligence side by side. It is considered necessary to study to redefine the direction and identity of arts and theater that should be moved forward.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.69-77
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• 1991

A collision-free trajectory planning algorithm using an iterative learning concept is proposed for dual robot arms in a 3-D common workspace to accurately follow their specified paths with constant velocities. Specifically, a collision-free trajectory minimizing the trajectory error is obtained first by employing the linear programming technique. Then the total operating time is iteratively adjusted based on the maximum trajectory error of the previous iteration so that the collision-free trajectory has no deviation from the specified path and also that the operating time is near-minimal. To show the validity of the proposed algorithm, a numerical example is presented based on two planar robots.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.52-57
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• 2014

This paper presents an implementation of a smooth path planning method considering physical limits on a real time operating system for a two-wheel mobile robot. A Bezier curve is utilized to make a smooth path considering a robot's position and direction angle through the defined path. A convolution operator is used to generate the center velocity trajectory to travel the distance of the planned path while satisfying the physical limits. The joint space velocity is computed to drive the two-wheel mobile robot from the center velocity. Trajectory planning, velocity command according to the planned trajectory, and monitoring of encoder data are implemented with a multi-tasking system. And the synchronization of tasks is performed with a real-time mechanism of Event Flag. A real time system with multi-tasks is implemented and the result is compared with a non-real-time system in terms of path tracking to the designed path. The result shows the usefulness of a real-time multi-tasking system to the control system which requires real-time features.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.31-40
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• 2009

The most common cleaning methods of cleaning robot can be divided into two categories: the random and the boustrophedon method. A cleaning robot using the random method moves straight until it bumps into an obstacle. If it collides with an obstacle, the cleaning robot turns a specific angle and continues moving straight. Therefore, the random method often tends to clean the already clean area repeatedly. In addition, it takes a long time to complete cleaning. A cleaning robot using the boustrophedon method moves straight until it collides with an obstacle. If it meets an obstacle, the cleaning robot moves to the next uncleaned space through turning and moving ahead. when resuming cleaning from the new region, a cleaning robot moves in the direction opposite to the direction of the previous cleaning. Because the boustrophedon method cleans a cleaning space more densely, its performance is excellent in an obstacle-free space or a small space. However, In a space with obstacles or a complex structure, it takes a long time to complete the cleaning work. Cleaning should be systematically approached with a good understanding of the work area. The virtual map-based cleaning robot proposed in this paper cleaned a work space efficiently. The efficiency of the proposed method was measured through simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.223-226
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• 2006

매니퓰레이션 기술 중에서 경로 계획은 중요한 문제 중의 하나이다. RRT는 경로 계획 알고리즘으로 최근에 제안되었다. RRT는 기존 알고리즘보다 빠르게 장애물을 회피하여 경로를 계획할 수 있다. 기존의 경로 계획 알고리즘은 그 상황에 따라 반복적으로 경로 계획을 하였다. 이러한 점을 개선하기위해 RRT와 인간의 소뇌구조를 모방한 CMAC을 결합한 CMACRRT를 제안한다. CMAC은 RRT가 만들어낸 경로와 그 상황을 기억하여 유사한 상황에서 경로를 다시 사용할 수 있게 해준다. 이렇게해서서 CMAC을 통해 학습된 상황에서 RRT를 사용하지 않고 기존의 경로를 사용할 수 있게 된다.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.164-172
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• 2019

In this paper, we implement a wheeled mobile robot that accurately and autonomously finds the optimal route from the starting point to the destination point based on computer vision in a complex indoor environment. We get a number of waypoints from the starting point to get the best route to the target through deep reinforcement learning. However, in the case of autonomous driving, the majority of cases do not reach their destination accurately due to external factors such as surface curvature and foreign objects. Therefore, we propose an algorithm to deepen the waypoints and destinations included in the planned route and then correct the route through the waypoint recognition while driving to reach the planned destination. We built an autonomous wheeled mobile robot controlled by Arduino and equipped with Raspberry Pi and Pycamera and tested the planned route in the indoor environment using the proposed algorithm through real-time linkage with the server in the OSX environment.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.8
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• pp.907-914
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• 2014

A heuristic search algorithm is proposed to plan a collision free path for robots in an indoor environment. The proposed algorithm is to find a collision free path in the gridded configuration space by proposed heuristic graph search algorithm. The proposed algorithm largely consists of two parts : tunnel searching and path searching in the tunnel. The tunnel searching algorithm finds a thicker path from start grid to goal grid in grid configuration space. The tunnel is constructed with large grid defined as a connected several minimum size grids in grid-based configuration space. The path searching algorithm then searches a path in the tunnel with minimum grids. The computational time of the proposed algorithm is less than the other graph search algorithm and we analysis the time complexity. To show the validity of the proposed algorithm, some numerical examples are illustrated for robot.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.159-159
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• 2000

최근 조선분야의 경우 생산원가의 절감, 품질의 고급화, 단순작업에 대한 근로기피 등의 이유로 로봇시스템 적용에 대한 필요성이 크게 대두되고 있다. 그러나 기존의 로봇 시스템의 교시방식이 교시-재생(Teaching-Playback)방식이어서 작업부재의 형상 및 치수가 매번 변경되는 중공업 분야에서는 적용이 불가능하였다. 본 연구에서는 조선용 아크용접 로봇을 위한 오프라인 프로그램밍(OLP: Off-Line Programming) 시스템을 개발하였다. 오프라인 프로그램밍 시스템의 경우 작업중인 로봇과는 상관없이 다음 부재에 대한 형상 데이터만을 이용하여 컴퓨터상에서 다음 작업프로그램을 미리 생성할 수 있으므로 기존의 온라인 교시-재생 방식의 교시시간의 과다라는 문제를 극복할 수 있다. 본 연구에서는 강교 판넬 및 조선 소조립용으로 개발 중인 아크용접용 로봇 시스템을 위한 오프라인 프로그래밍 시스템을 개발하였다. CAD 데이터나 OLP의 모델링 기능으로 작업부재를 형상한 후 미리 데이터베이스화 되어 있는 자료를 검색하여 부위별 작업매크로 확보를 위하여 실제 로봇 시스템을 이용한 작업테스트를 수행하였다. 개발된 오프라인 프로그래밍 시스템은 기능보완 후 당사 아크용접용 로봇시스템에 적용될 계획이다.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.325-326
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• 2007

인간형 로봇(Humanoid)은 인간과 유사한 구조를 갖고 있는 로봇으로, 이족 보행이 가능하고 양 손이 자유롭기 때문에 인간 생활 환경에 적용이 가능하다. 인간형 로봇은 이족 보행 로봇의 형태를 지니며 보통 20 자유도(DOF : Degree of freedom) 이상의 높은 자유도와 직렬형 링크 구조로 인해 로봇의 안정도를 해석하고 움직임을 제어하기가 어렵다. 이러한 이유로 이족 보행 로봇 동작의 안정도를 증가시키기 위해 로봇의 최적화된 동작 패턴 생성과 자세 제어 등이 연구 되고 있다. 본 논문에서는 범용 근사자의 특징을 갖는 신경망을 이용하여 이족 보행 로봇의 동작 패턴 생성 방법에 대하여 제안하였다. 실제로 계획된 동작을 토대로 6가지의 동작 패턴을 생성하였으며 컴퓨터 모의실험과 상용 이족 보행 로봇을 이용하여 생성된 동작 패턴의 안정도를 확인해보고 제안된 방법에 타당성을 검증하였다.