• Title/Summary/Keyword: control arm

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Implementation of IEEE 802.11ac Down-link MU-MIMO WLAN MAC using Unified Design Methodology

  • Chung, Chulho;Jung, Yunho;Kim, Jaeseok
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.16 no.6
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    • pp.719-727
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    • 2016
  • This paper proposes a unified medium access control (MAC) design methodology and presents the implementation of the IEEE 802.11ac down-link multi-user multi-input and multi-output wireless local area network MAC using the proposed design methodology. The proposed methodology employs unified code for both network simulation and system implementation. Because the unified code closely relates these two processes, the performance of the implemented MAC system can be estimated before implementation. The MAC architecture for an access point implemented using the proposed design methodology is verified on an ARM-based platform, and it is applied to a 65 nm CMOS library.

Neural Oscillator based Two-link Robot Arm Control (Neural Oscillator 특성을 활용한 2축 링크 로봇 팔 제어)

  • Kwon, J.S.;Yang, W.;Park, G.T.;You, B.J.
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.1813-1814
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    • 2008
  • 본 논문에서는 생물학적 운동 메카니즘을 유사하게 구현하기 위해 신경 진동자를 이용한 로봇 팔 제어 시스템을 제안한다. 인간 및 동물의 주기적인 자율 운동을 관장하는 Central Pattern Generator (CPG)를 수학적으로 모델링한 신경 진동자는 그 중요 특성의 하나인 entrainment 효과를 보여준다. 일반적으로 우리는 이 기능을 이용하여 미지의 외부 환경 변화와 같은 외란에 적절히 상호 작용할 수 있는 운동을 생성해 낼 수 있다. 이러한 결과를 보이기 위해, 각 관절에 가상의 신경 진동자 모델을 결합하였고 외부 환경의 변화나 외란의 감지를 위한 F/T센서를 팔의 말단에 부착하여 시스템을 구현하였다. 신경 진동자 모델을 결합한 2축 링크 로봇 팔 시스템(real time)은 주어진 목적운동을 (원 운동) 수행함과 동시에 미지의 외부 환경의 변화(임의의 벽)를 인지하여 적절한 모션을 생성하는 지를 살펴본다.

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Vision-Based Robot Manipulator for Grasping Objects (물체 잡기를 위한 비전 기반의 로봇 메뉴플레이터)

  • Baek, Young-Min;Ahn, Ho-Seok;Choi, Jin-Young
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.331-333
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    • 2007
  • Robot manipulator is one of the important features in service robot area. Until now, there has been a lot of research on robot" manipulator that can imitate the functions of a human being by recognizing and grasping objects. In this paper, we present a robot arm based on the object recognition vision system. We have implemented closed-loop control that use the feedback from visual information, and used a sonar sensor to improve the accuracy. We have placed the web-camera on the top of the hand to recognize objects. We also present some vision-based manipulation issues and our system features.

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The design of the remote control Crabster robotic arm (Crabseter 로봇팔의 원격 제어기 설계)

  • Choi, Hyeung-Sik;Jeong, Sang-Ki;Uhm, Tai-Woong;Loc, Mai Ba;Kim, Joon-Young
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2011.10a
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    • pp.77-78
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    • 2011
  • 한국해양연구원에서 개발 중인 Crabster 로봇팔을 기구학적으로 분석하고, 속도기구학을 매트랩을 이용하여 작업공간에 대해서도 분석 및 해석을 완료하였다. 운용자와 Crabster 로봇팔의 움직임을 고려해 개념 설계한 인간팔 크기의 7축 마스터 암 및 그립퍼의 기구부에 대해 2D 및 3D의 도면을 완성하였고, 마스터 암에 적용할 모터의 사양과 각 관절에 피드백 된 힘을 반영하기 위한 구동 모터의 엔코더를 이용한 위치 센서, DSP2812를 이용한 제어 명령 입력 장치와 구동 모터 드라이버를 포함한 마스터 - 슬레이브 시스템의 개념 설계를 완성하였다.

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The Examples of Weight Reduction Design-(2) (Weight Reduction Design의 선례-(2))

  • Lee, Jeong-Ick
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.15 no.6
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    • pp.97-104
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    • 2006
  • The geometric configuration in the weight reduction designis very required to be started from the conceptual design with low cost, high performance and quality. In this point, a structural-topological shape concerned with conceptual design of structure is important. The method used in this paper combines three optimization techniques, where the shape and physical dimensions of the structure and material distribution are hierachically optimized, with the maximum rigidity of structure and lightweight. As the results, the technology of weight reduction design is considered in designs of aluminum control arm and inner panel of door.

Study on Design of Fingerprint Recognition Embedded System using Neural Network (신경망을 이용한 지문인식 임베디드 시스템 설계에 관한 연구)

  • Lee Jae-Hyun;Kim Dong-Han
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.4
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    • pp.775-782
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    • 2006
  • We generated blocks from the direction-extracted fingerprint during the pre-process of the fingerprint recognition algorithm and performed training by using the direction minutiae of each block as the input pattern of the neural network, so that we extracted the core points to use in the matching. Based on this, we designed the fingerprint recognition embedded system and tested it using the control board and the serial communication to utilize it for a variety of application systems. As a result, we can verify the reliance satisfactorily.

동적 보상기를 갖는 가벼운 유연성 매니퓰레이터의 적응 제어

  • 김승록;박종국
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.15 no.8
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    • pp.708-714
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    • 1990
  • This paper has proposed a self-tuning controller for tracking reference trajectory by measuring End-point of arm on robot manipulator whose link is light and flexibls, and proved the perforformance of the algorithm proposed through the computer simulation. As an object of control, a flexible robot manipulator with two-links was selected. As for structure of model, it utilized an assume mode shape method with include travity force and derived a dynaics equation by adapting two kinds of vibration mode of each.

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Hand/Eye calibration of Robot arms with a 3D visual sensing system (3차원 시각 센서를 탑재한로봇의 Hand/Eye 캘리브레이션)

  • 김민영;노영준;조형석;김재훈
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.76-76
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    • 2000
  • The calibration of the robot system with a visual sensor consists of robot, hand-to-eye, and sensor calibration. This paper describe a new technique for computing 3D position and orientation of a 3D sensor system relative to the end effect of a robot manipulator in an eye-on-hand robot configuration. When the 3D coordinates of the feature points at each robot movement and the relative robot motion between two robot movements are known, a homogeneous equation of the form AX : XB is derived. To solve for X uniquely, it is necessary to make two robot arm movements and form a system of two equation of the form: A$_1$X : XB$_1$ and A$_2$X = XB$_2$. A closed-form solution to this system of equations is developed and the constraints for solution existence are described in detail. Test results through a series of simulation show that this technique is simple, efficient, and accurate fur hand/eye calibration.

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Measurement Time-Delay Error Compensation For Transfer Alignment

  • Lim, You-Chol;Song, Ki-Won;Joon Lyou
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.486-486
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    • 2000
  • This paper is concerned with a transfer alignment method for the SDINS(StrapDown Inertial Navigation System) under ship motions. Major error sources of transfer alignment are data transfer time-delay, lever-arm velocity and ship body flexure. Specifically, to reduce alignment errors induced by measurement time-delay effects, the error compensation method through delay state augmentation is suggested. A linearized error model for the velocity and attitude matching transfer alignment system is first derived by linearizing the nonlinear measurement equation with respect to its time delay and augmenting the delay state into the conventional linear state equations. And then it is shown via observability analysis and computer simulations that the delay state can be estimated and compensated during ship motions resulting in considerably less alignment errors.

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Hand Reaching Movement Acquired through Reinforcement Learning

  • Shibata, Katsunari;Sugisaka, Masanori;Ito, Koji
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.474-474
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    • 2000
  • This paper shows that a system with two-link arm can obtain hand reaching movement to a target object projected on a visual sensor by reinforcement learning using a layered neural network. The reinforcement signal, which is an only signal from the environment, is given to the system only when the hand reaches the target object. The neural network computes two joint torques from visual sensory signals, joint angles, and joint angular velocities considering the urn dynamics. It is known that the trajectory of the voluntary movement o( human hand reaching is almost straight, and the hand velocity changes like bell-shape. Although there are some exceptions, the properties of the trajectories obtained by the reinforcement learning are somewhat similar to the experimental result of the human hand reaching movement.

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