• Title/Summary/Keyword: Robot Control Scheme

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An Efficient Localization of Mobile Robot in RFID Sensor Space (RFID 센서 공간에서의 모바일 로봇의 효율적인 위치 인식)

  • Choi, Byoung-Suk;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.1
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    • pp.15-22
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    • 2006
  • This paper presents an efficient localization scheme for an indoor mobile robot using RFID tags on the floor. The mobile robot carries an RFID reader at the bottom, which reads the RFID tags on the floor to localize the mobile robot. Each RFID tar on the floor stores its own absolute position which is used to calculate the position and velocity of the mobile robot. Locating the RFID tags on the floor, which constructs an intelligent sensor space, may require several factors to be considered: economics feasibility and accuracy. In this paper, the optimal allocation scheme of the RFID tags on the floor to satisfy the accuracy constraint has been proposed and verified by the experiments. Based on the RFID reading, the mobile robot navigation has been successfully demonstrated to avoid obstacles and to reach the goal within a pre-specified time.

Adaptive Control of Space Robot in Inertia Space (Inertia Space에서 우주 로봇의 적응제어)

  • Lee, Ju-Jang
    • Proceedings of the KIEE Conference
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    • 1992.07a
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    • pp.381-385
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    • 1992
  • In this paper, dynamic modeling and adaptive control problems for a space robot system are discussed. The space robot consist of a robot manipulator mounted on a free-floating base where no attitude control is applied. Using an extended robot model, the entire space robot can be viewed as an under-actuated robot system. Based on nonlinear control theory, the extended space robot model can then be decomposed into two subsystems: one is input-output exactly linearizable, and the other is unlinearizable and represents an internal dynamics. With this decomposition, a normal form-augmentation approach and an augmented state-feedback control are proposed to facilitate the design of adaptive control for the space robot system against parameter uncertainty, unknown dynamics and unmodeled payload in space applications. We demonstrate that under certain conditions, the entire space robot can be represented as a full-actuated robot system to avoid the inclusion of internal dynamics. Based on the dynamic model, we propose an adaptive control scheme using Cartesian space representation and demonstrate its validity and design procedure by a simulation study.

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Cooperative Control of the Multi-Agent System for Teleoperation (원격조종 다개체 로봇의 협동제어)

  • 황정훈;권동수
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.154-154
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    • 2000
  • The cooperative strategy for the teleoperated multi-agent system is presented. And this scheme has been applied to the teleoperated robot soccer system that is newly proposed. For the teleoperated robot soccer system, we made mapping functions to control a 2-wheeled mobile robot using a 2 DoF stickcontroller. The simulation with a real stickcontroller has been evaluated the performance of the proposed mapping function. Then, the basic cooperation strategy has been tested between teleoperated robot and autonomous robot It is shown that the multi-agent system for teleoperation can have a good performance for a job Like a scoring a goal

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Implementation of a Learning Controller for Repetitive Gate Control of Biped Walking Robot (이족 보행 로봇의 반복 걸음새 제어를 위한 학습제어기의 구현)

  • Lim, Dong-Cheol;Oh, Sung-Nam;Kuc, Tae-Yong
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.594-596
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    • 2005
  • This paper present a learning controller for repetitive gate control of biped robot. The learning control scheme consists of a feedforward learning rule and linear feedback control input for stabilization of learning system. The feasibility of learning control to biped robotic motion is shown via dynamic simulation and experimental results with 24 DOF biped robot.

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A Sliding Mode Controller Using Neural Network for Underwater Robot Manipulator (해저작업 로봇 매니퓰레이터를 위한 신경회로망을 이용한 슬라이딩 모드 제어기)

  • Lee, Min-Ho;Choi, Hyung-Sik
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.4
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    • pp.305-312
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    • 2000
  • This paper presents a new control scheme using a sliding mode controller with a multilayer neural network for the robot manipulator operating under the sea which has large uncertainties such as the buoyancy and the added mass/moment of inertia. The multilayer neural network using the error back propagation loaming algorithm acts as a compensator of the conventional sliding mode controller to improve the control performance when the initial assumptions of uncertainty bounds are not valid. Computer simulation results show that the proposed control scheme gives an effective path way to cope with the unexpected large uncertainties in the underwater robot manipulator.

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A Study on Robust Controller Design of Multi-Joint Robot Manipulator Using Adaptive Control (적응제어기법에 의한 다관절 로보트 매니퓰레이터의 견실한 제어기 설계에 관한 연구)

  • Han, Sung-Hyun;Lee, Man-Hyung
    • Journal of the Korean Society for Precision Engineering
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    • v.6 no.4
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    • pp.108-118
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    • 1989
  • An adaptive control scheme has been recognized as an effective approach for a robot manipulator to track a desired trajectory in spite of the presence of nonliearity and parameter uncertainty in robot dynamics model. In this paper, an adaptive control scheme for a robot manipulator is proposed to design robust controller using model reference adaptive control technique and hyperstability theory but it does away with] assumption that the process is characterized by a linear model remaining time invariant during the adaptation process. The performance of controller is demonstrated by the simulation about position and speed control of a six-link manipulator with disturbance and payload variation.

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The Design of Fuzzy-Neural Controller for Velocity and Azimuth Control of a Mobile Robot (이동형 로보트의 속도 및 방향제어를 위한 퍼지-신경제어기 설계)

  • Han, S.H.;Lee, H.S.
    • Journal of the Korean Society for Precision Engineering
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    • v.13 no.4
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    • pp.75-86
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    • 1996
  • In this paper, we propose a new fuzzy-neural network control scheme for the speed and azimuth control of a mobile robot. The proposed control scheme uses a gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the frame-work of the specialized learning architecture. It is proposed a learning controller consisting of two fuzzy-neural networks based on independent reasoning and a connection net woth fixed weights to simply the fuzzy-neural network. The effectiveness of the proposed controller is illustrated by performing the computer simulation for a circular trajectory tracking of a mobile robot driven by two independent wheels.

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Variable structure model following control for robot manipulator using time-varying sliding hyperplane

  • Park, Kang-Bark;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.519-523
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    • 1993
  • In this paper, the variable structure model following control scheme is proposed for the nonlinear robot manipulator system. The proposed control system guarantees that the system state is in the sliding mode for all time. Therefore, error transient can be prescribed in advance for all time. Furthermore, overall system is globally exponentially stable. Chattering problem is reduced by the introduction of a boundary layer. Simulation results are given to show the usefulness of the proposed control scheme.

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A Trajectory Tracking Control of Wheeled Mobile Robot Using a Model Reference Adaptive Fuzzy Controller (모델참조 적응 퍼지제어기를 이용한 휠베이스 이동 로봇의 궤적 추적 제어)

  • Kim, Seung-Woo;Seo, Ki-Sung;Cho, Young-Wan
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.7
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    • pp.711-719
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    • 2009
  • This paper presents a design scheme of torque control for wheeled mobile robot(WMR) to asymptotically track the target reference trajectory. By considering the kinematic model of WMR, trajectory tracking control generates the desired tracking trajectory, which is transformed into the command velocity vector for the real WMR to track the target reference trajectory. The dynamic equation of the state error between the target reference trajectory and the desired tracking trajectory is represented by Takagi-Sugeno fuzzy model, and this model is used as the reference model for the real mobile robot error dynamics to follow. The control parameters are updated by adaptive laws that are designed for the error states of the real WMR to asymptotically follow the states of reference error model for the desired tracking trajectory. The proposed control is applied to a typical wheeled mobile robot and simulation studies are carried out to verify the validity and effectiveness of the control scheme.