• Title/Summary/Keyword: robot systems

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An Operating Software Architecture for PC-based (PC기반의 생산시스템을 위한 운용소프트웨어 구조)

  • Park, Nam-Jun;Kim, Hong-Seok;Park, Jong-Gu
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.1
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    • pp.1196-1204
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    • 2001
  • In this paper, a new architecture of operating software associated with the component-based method is proposed. The proposed architecture comprises 문 execution module and a decision-making module. In order to make effective development and maintenance, the execution module is divided into three components. The components are referred to as Symbol, Gateway, and Control, respectively: The symbol component is for the GUI environments and the standard interfaces; the gateway component is for the network communication and the structure of asynchronous processes; the control component is for the asynchronous processing and machine setting or operations. In order to verify the proposed architecture, and off-line version of operating software is made, and its steps are as follows; I) Make virtual execution modules for the manufacturing devices such as dual-arm robot, handling robot, CNC, and sensor; ii) Make decision-making module; iii) Integrate the modules and GUI using a well-known development tools such as Microsofts Visual Basic; iv) Execute the overall operating software to validate the proposed architecture. The proposed software architecture in this paper has the advantages such as independent development of each module, easy development of network communication, and distributed processing of resources, and so on.

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Recognition of the Center Position of Bolt Hole in the Stand of Insulator Using Multilayer Neural Network (다층 뉴럴네트워크를 이용한 애자 스탠드에서의 볼트 구멍의 중심위치 인식)

  • 안경관;표성만
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.4
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    • pp.304-309
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    • 2003
  • Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system. In order to realize these tasks autonomously, the three dimensional position of target object such as electric line and the stand of insulator must be recognized accurately and rapidly. The approaching of an insulator and the wrenching of a nut task is selected as the typical task of the maintenance of active electric power distribution lines in this paper. Image recognition by multilayer neural network and optimal target position calculation method are newly proposed in order to recognize the center 3 dimensional position of the bolt hole in the stand of insulator. By the proposed image recognition method, it is proved that the center 3 dimensional position of the bolt hole can be recognized rapidly and accurately without regard to the pose of the stand of insulator. Finally the approaching and wrenching task is automatically realized using 6-link electro-hydraulic manipulators.

On a Multi-Agent System for Assisting Human Intention

  • Tawaki, Hajime;Tan, Joo Kooi;Kim, Hyoung-Seop;Ishikawa, Seiji
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1126-1129
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    • 2003
  • In this paper, we propose a multi-agent system for assisting those who need help in taking objects around him/her. One may imagine this kind of situation when a person is lying in bed and wishes to take an object on a distant table that cannot be reached only by stretching his/her hand. The proposed multi-agent system is composed of three main independent agents; a vision agent, a robot agent, and a pass agent. Once a human expresses his/her intention by pointing to a particular object using his/her hand and a finger, these agents cooperatively bring the object to him/her. Natural communication between a human and the multi-agent system is realized in this way. Performance of the proposed system is demonstrated in an experiment, in which a human intends to take one of the four objects on the floor and the three agents successfully cooperate to find out the object and to bring it to the human.

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Trend of Soft Wearable Robotic Hand (유연한 착용형 손 로봇 기술 동향)

  • In, Hyunki;Jeong, Useok;Kang, Brian Byunghyun;Lee, Haemin;Koo, Inwook;Cho, Kyu-Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.6
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    • pp.531-537
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    • 2015
  • Hand function is one of the essential functions required to perform the activities of daily living, and wearable robots that assist or recover hand functions have been consistently developed. Previously, wearable robots commonly employed conventional robotic technology such as linkage which consists of rigid links and pin joints. Recently, as the interest in soft robotics has increased, many attempts to develop a wearable robot with a soft structure have been made and are in progress in order to reduce size and weight. This paper presents the concept of a soft wearable robot composed of a soft structure by comparing it with conventional wearable robots. After that, currently developed soft wearable robots and related issues are introduced.

Path Planning for a Robot Manipulator based on Probabilistic Roadmap and Reinforcement Learning

  • Park, Jung-Jun;Kim, Ji-Hun;Song, Jae-Bok
    • International Journal of Control, Automation, and Systems
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    • v.5 no.6
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    • pp.674-680
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    • 2007
  • The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

Observation Likelihood Function Design and Slippage Error Compensation Scheme for Indoor Mobile Robots (실내용 이동로봇을 위한 위치추정 관측모델 설계 및 미끄러짐 오차 보상 기법 개발)

  • Moon, Chang-Bae;Kim, Kyoung-Rok;Song, Jae-Bok;Chung, Woo-Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.11
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    • pp.1092-1098
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    • 2007
  • A mobile robot localization problem can be classified into following three sub-problems as an observation likelihood model, a motion model and a filtering technique. So far, we have developed the range sensor based, integrated localization scheme, which can be used in human-coexisting real environment such as a science museum and office buildings. From those experiences, we found out that there are several significant issues to be solved. In this paper, we focus on three key issues, and then illustrate our solutions to the presented problems. Three issues are listed as follows: (1) Investigation of design requirements of a desirable observation likelihood model, and performance analysis of our design (2) Performance evaluation of the localization result by computing the matching error (3) The semi-global localization scheme to deal with localization failure due to abrupt wheel slippage In this paper, we show the significance of each concept, developed solutions and the experimental results. Experiments were carried out in a typical modern building environment, and the results clearly show that the proposed solutions are useful to develop practical and integrated localization schemes.

Iterative learning control for discrete-time feedback systems and its applicationto a direct drive SCARA robot (이산시간 궤환 시스템에 대한 반복학습제어 및 직접구동형 SCARA 로보트에의 응용)

  • Yeo, Seong-Won;Kim, Jae-Oh;Hwang, Gun;Kim, Sung-Hyun;Kim, Do-Hyun;Ahn, Hyun-Sik
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.7
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    • pp.56-65
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    • 1997
  • In this paper, we propose a reference input odification-type iterative learning control law for a class of discrete-time nonlinear systems and prove the convergence of the output error. We can get the high-precision in case of the trajectroy control when the proposed control law is properly combined with a feedback controller, and we can easily implement the learning control law compared to the control input modification-type learning control law. To show the validity and the convergence perfodrmance of the proposed control law, we perform experimentations on the trajectroy control and rejection of periodic disturbance for a 2-axis SCARA-type direct drive robot.

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Finite-Time Sliding Mode Controller Design for Formation Control of Multi-Agent Mobile Robots (다중 에이전트 모바일 로봇 대형제어를 위한 유한시간 슬라이딩 모드 제어기 설계)

  • Park, Dong-Ju;Moon, Jeong-Whan;Han, Seong-Ik
    • The Journal of Korea Robotics Society
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    • v.12 no.3
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    • pp.339-349
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    • 2017
  • In this paper, we present a finite-time sliding mode control (FSMC) with an integral finite-time sliding surface for applying the concept of graph theory to a distributed wheeled mobile robot (WMR) system. The kinematic and dynamic property of the WMR system are considered simultaneously to design a finite-time sliding mode controller. Next, consensus and formation control laws for distributed WMR systems are derived by using the graph theory. The kinematic and dynamic controllers are applied simultaneously to compensate the dynamic effect of the WMR system. Compared to the conventional sliding mode control (SMC), fast convergence is assured and the finite-time performance index is derived using extended Lyapunov function with adaptive law to describe the uncertainty. Numerical simulation results of formation control for WMR systems shows the efficacy of the proposed controller.

Localization and 3D Polygon Map Building Method with Kinect Depth Sensor for Indoor Mobile Robots (키넥트 거리센서를 이용한 실내 이동로봇의 위치인식 및 3 차원 다각평면 지도 작성)

  • Gwon, Dae-Hyeon;Kim, Byung-Kook
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.9
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    • pp.745-752
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    • 2016
  • We suggest an efficient Simultaneous Localization and 3D Polygon Map Building (SLAM) method with Kinect depth sensor for mobile robots in indoor environments. In this method, Kinect depth data is separated into row planes so that scan line segments are on each row plane. After grouping all scan line segments from all row planes into line groups, a set of 3D Scan polygons are fitted from each line group. A map matching algorithm then figures out pairs of scan polygons and existing map polygons in 3D, and localization is performed to record correct pose of the mobile robot. For 3D map-building, each 3D map polygon is created or updated by merging each matched 3D scan polygon, which considers scan and map edges efficiently. The validity of the proposed 3D SLAM algorithm is revealed via experiments.

Robust Visual Odometry System for Illumination Variations Using Adaptive Thresholding (적응적 이진화를 이용하여 빛의 변화에 강인한 영상거리계를 통한 위치 추정)

  • Hwang, Yo-Seop;Yu, Ho-Yun;Lee, Jangmyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.9
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    • pp.738-744
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    • 2016
  • In this paper, a robust visual odometry system has been proposed and implemented in an environment with dynamic illumination. Visual odometry is based on stereo images to estimate the distance to an object. It is very difficult to realize a highly accurate and stable estimation because image quality is highly dependent on the illumination, which is a major disadvantage of visual odometry. Therefore, in order to solve the problem of low performance during the feature detection phase that is caused by illumination variations, it is suggested to determine an optimal threshold value in the image binarization and to use an adaptive threshold value for feature detection. A feature point direction and a magnitude of the motion vector that is not uniform are utilized as the features. The performance of feature detection has been improved by the RANSAC algorithm. As a result, the position of a mobile robot has been estimated using the feature points. The experimental results demonstrated that the proposed approach has superior performance against illumination variations.