• Title/Summary/Keyword: mobile control

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A Self-Organizing Fuzzy Control Approach to the Driving Control of a Mobile Robot (자기구성 퍼지제어기를 이용한 이동로봇의 구동제어)

  • Bae, Kang-Yul
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.12 s.189
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    • pp.46-55
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    • 2006
  • A robust motion controller based on self-organizing fuzzy control(SOFC) and feed-back tracking control technique is proposed for a two-wheel driven mobile robot. The feed-back control technique of the controller guarantees the robot follows a desired trajectory. The SOFC technique of the controller deals with unmodelled dynamics of the vehicle and uncertainties. The computer simulations are carried out to verify the tracking ability of the proposed controller with various driving situations. The results of the simulations reveal the effectiveness and stability of the proposed controller to compensate the unmodelled dynamics and uncertainties.

Adaptive Sliding-Mode Formation Control and Collision Avoidance for Multi-agent Nonholonomic Mobile Robots with Model Uncertainty and Disturbance (모델 불확실성 및 외란을 갖는 이동 로봇들을 위한 적응 슬라이딩 모드 군집 제어 및 충돌 회피 기법)

  • Park, Bong-Seok;Park, Jin-Bae
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.11
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    • pp.1038-1043
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    • 2010
  • In this paper, an adaptive sliding-mode formation control and collision avoidance are proposed for electrically driven nonholonomic mobile robots with model uncertainties and external disturbances. A sliding surface based on the leader-follower approach is developed to achieve the desired formation in the presence of model uncertainties and disturbances. Moreover, by using the collision avoidance function, the mobile robots can avoid the obstacles successfully. Finally, simulations illustrate the effectiveness of the proposed control system.

Dynamic control of mobile robots using a robust.adaptive learning control method (강인.적응학습제어 방식에 의한 이동로봇의 동력학 제어)

  • Nam, Jae-Ho;Baek, Seung-Min;Guk, Tae-Yong
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.2
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    • pp.178-186
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    • 1998
  • In this paper, a robust.adaptive learning control scheme is presented for precise trajectory tracking of rigid mobile robots. In the proposed controller, a set of desired trajectories is defined and used in constructing the control input and learning rules which constitute the main part of the proposed controller. Stable operating characteristics such as precise trajectory tracking, parameter estimation, disturbance suppression, etc., are shown thorugh experiments and computer simulations.

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Leader-Following Based Adaptive Formation Control for Multiple Mobile Robots (다개체 이동 로봇을 위한 선도-추종 접근법 기반 적응 군집 제어)

  • Park, Bong-Seok;Park, Jin-Bae
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.5
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    • pp.428-432
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    • 2010
  • In this paper, an adaptive formation control based on the leader-following approach is proposed for multiple mobile robots with time varying parameters. The proposed controller does not require the velocity information of the leader robot, which is commonly assumed that it is either measured or telecommunicated. In order to estimate time varying velocities of the leader robot, the smooth projection algorithm is employed. From the Lyapunov stability theory, it is proved that the proposed control scheme can guarantee the uniform ultimate boundedness of error signals of the closed-loop system. Finally, the computer simulations are performed to demonstrate the performance of the proposed control system.

Polynomial Fuzzy Modelling and Trajectory Tracking Control of Wheeled Mobile Robots with Input Constraint (입력제한을 고려한 이동로봇의 다항 퍼지모델링 및 궤적추적제어)

  • Kim, Cheol-Joong;Chwa, Dong-Kyoung;Oh, Seong-Keun;Hong, Suk-Kyo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.9
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    • pp.1827-1833
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    • 2009
  • This paper deals with the trajectory tracking control of wheeled mobile robots with input constraint. The proposed method converts the trajectory tracking problem to the system stability problem using the control inputs composed of feedforward and feedback terms, and then, by using Taylor series, nonlinear terms in origin system are transformed into polynomial equations. The composed system model can make it possible to obtain the control inputs using numerical tool named as SOSTOOL. From the simulation results, the mobile robot can track the reference trajectory well and can have faster convergence rate of the trajectory errors than the existing nonlinear control method. By using the proposed method, we can easily obtain the control input for nonlinear systems with input constraint.

Autonomous Wall-Following of Wheeled Mobile Robots using Hybrid Control Approach (차륜형 이동로봇의 자율 벽면-주행을 위한 하이브리드 제어)

  • Lim, Mee-Seub;Lim, Joon-Hong;Oh, Sang-Rok
    • Proceedings of the KIEE Conference
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    • 1999.07g
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    • pp.3105-3107
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    • 1999
  • In this paper, we propose a new approach to autonomous wall-following of wheeled mobile robots using hybrid control system. The hybrid control approach IS introduced to the motion control of nonholonomic mobile robots in the Indoor navigation problems. In hybrid control architecture, the discrete states are defined by the user-defined constraints, and the reference motion commands are specified In the abstracted motions. The hybrid control system applied to motion planning and autonomous navigation with obstacle avoidance In indoor navigation problem. Simulation results show that it is an effective method for the autonomous navigation in indoor environments.

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Control Gain Optimization for Mobile Robots Using Neural Networks and Genetic Algorithms (신경회로망과 유전알고리즘에 기초한 이동로봇의 제어 이득 최적화)

  • Choi, Young-kiu;Park, Jin-hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.4
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    • pp.698-706
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    • 2016
  • In order to move mobile robots to desired locations in a minimum time, optimal control problems have to be solved; however, their analytic solutions are almost impossible to obtain due to robot nonlinear equations. This paper presents a method to get optimal control gains of mobile robots using genetic algorithms. Since the optimal control gains of mobile robots depend on the initial conditions, the initial condition range is discretized to form some grid points, and genetic algorithms are applied to provide the optimal control gains for the corresponding grid points. The optimal control gains for general initial conditions may be obtained by use of neural networks. So the optimal control gains and the corresponding grid points are used to train neural networks. The trained neural networks can supply pseudo-optimal control gains. Finally simulation studies have been conducted to verify the effectiveness of the method presented in this paper.

A Precise Localization Method for a High Speed Mobile Robot using iGS and Dual Compass (iGS와 듀얼 컴퍼스를 이용한 고속 이동로봇의 정밀 위치 인식기법)

  • Jang, Won-Seok;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.12
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    • pp.1182-1188
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    • 2010
  • This paper proposes a precise localization algorithm for a quickly moving mobile robot. In order to localize a mobile robot with active beacon sensors, a relatively long time is needed, since the distance to the beacon is measured using the flight time of the ultrasonic signal. The measurement time does not cause a high error rate when the mobile robot moves slowly. However, with an increase of the mobile robot's speed, the localization error becomes too high to use for accurate mobile robot navigation. Therefore, in this research into high speed mobile robot operations, instead of using two active beacons for localization an active beacon and dual compass are utilized to localize the mobile robot. This new approach resolves the high localization error caused by the speed of the mobile robot. The performance of the precise localization algorithm was verified by comparing it to the conventional method through real-world experiments.