• Proceedings of the KSME Conference
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• 2000.04a
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• pp.511-516
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• 2000

In order to not only perform as a extreme model under the severe operating condition but also acquire more diverse and advanced control capability utilizing high compliance, active vibration control of a flexible 2-link robot manipulator are investigated. Multi variable-structured frequency shaped optimal sliding mode is proposed for the flexible robot manipulator like control system, whose control variables, an angular motion of joint and vibration of flexible link, have to be controlled simultaneously by one control torque at a driving joint. The control system is divided into two subsystems, a control input related subsystem and an added subsystem. The proposed sliding mode, composed of multi control variables, makes optimized relation between subsystems and a individual control input, thus, the sliding mode controller can compensate whole dynamics of each subsystems simultaneously. And the possibility and effectiveness are verified by vibration control of a manipulator having two flexible links. Simulation and experiment results show that the proposed control scheme achieves the purpose effectively.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.915-920
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• 2013

Payload capacity and transition ability are essential for climbing robots to apply the robots to various applications such as inspection and exploration. This paper presents a new climbing robotic platform with multi-link structure of track-wheel modules to enhance payload capacity and transition ability, and its tracking controller design and experimental results. The compliances between track-wheel modules achieve stable internal and external transitions while the large adhesion area of the track-wheel module enhances the payload capacity of the robot. Kinematic model-based tracking controller is designed and implemented for autonomous internal transition, and the gains of the controller are optimized by experimental design. Experiments on the automatic internal transitions are performed and the results guarantee autonomous internal transition with little tracking error.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.557-558
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• 2009

• Journal of Mechanical Science and Technology
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• v.18 no.4
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• pp.573-581
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• 2004

A self-contained wall climbing robot, called MRWALLSPECT (Multi-functional Robot for WALL inSPECTion) II, is developed. It is designed for scanning external surfaces of gas or oil tanks with small curvature in order to find defects. The robot contains all the components for navigation in itself without any external tether cable. Although it takes the basic structure of the sliding body mechanism, the robot has its original characteristic features in the kinematic design with closed link mechanism, which is enabled by adopting a simple and robust gait pattern mimicking a biological system. By employing the proposed link mechanism, the number of actuators is reduced and high force-to-weight ratio is achieved. This paper describes its mechanism design and the overall features including hardware and software components. Also, the preliminary results of experiments are given for evaluating its performances.

• International Journal of Ocean System Engineering
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• v.1 no.4
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• pp.222-229
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• 2011

In this paper, we present the concept and main mission of the Crabster, an underwater walking robot. The main focus is on the modeling of drag and lift forces on the legs of the robot, which comprise the main difference in dynamic characteristics between on-land and underwater robots. Drag and lift forces acting on the underwater link are described as a function of the relative velocity of the link with respect to the fluid using the strip theory. Using the translational velocity of the link as the rotational velocity of the joint, we describe the drag force as a function of joint variables. Generalized drag torque is successfully derived from the drag force as a function of generalized variables and its first derivative, even though the arm has a roll joint and twist angles between the joints. To verify the proposed model, we conducted drag torque simulations using a simple Selective Compliant Articulated Robot Arm.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.657-660
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• 2003

Control of multi-link robot arms is a very difficult problem because of the highly nonlinear dynamics. Decentralized control scheme is developed for control of robot manipulators based on RBF(Radial Basis Function) Neural Networks. RBF Neural Networks is used to approximate the coupling forces among the joints, coriolis force, centrifugal force, gravitational force, and frictional force. The compensation controller is also proposed to estimate the bound of approximation error so that the chattering effect of the control effort can be reduced. The proposed scheme does not require an accurate manipulator dynamic, and it is proved that closed-loop system is asymptotic stable despite the gross robot parameter variations. Numerical simulations for two-link robot manipulator are included to show the effectiveness of controller.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.3
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• pp.34-40
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• 2001

Robot manipulator has highly nonlinear dynamics. Therefore the control of multi-link robot arms is a challenging and difficult problem. In this paper a decentralized adaptive fuzzy sliding mode scheme is developed for control of robot manipulators. The proposed scheme does not require an accurate manipulator dynamic model, yet it guarantees asymptotic trajectory tracking despite gross robot parameter variations. Numerical simulation for decentralized control of a 3-axis PUMA arm will also be included.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.518-521
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• 1995

In this paper, a learning control problem is formulated for cooperating multiple-robot manipulators with uncertain system parameters. The commonly held object is also assumed to be unknown and the multiple-robots themselfs experience uncertain operating conditions such as link parameters, viscous friction parameters, suctions, actuator bias, and etc. Under these conditions, the learning controllers designed for learning of uncertain parameters and robot control inputs for multiple-robot systems are shown to drive the multiple-robot manipulators to follow the desired Cartesian trajectory with the desired internal forces to the unknown object.

• Journal of Animal Environmental Science
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• v.13 no.3
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• pp.179-186
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• 2007

The purpose of this study was kinematics analysis of the multi-joint robot manipulator for an automatic milking system. The multi-joint robot manipulator was consisted of one perpendicular link and four revolution links to attach simultaneously four teat cups to four teats of a milking cow. The local coordinates of each joints on the robot manipulator was given for kinematics analysis. The transformation of manipulator was able to be given by kinematics using Denavit-Hatenberg parameters. The value of inverse kinematics which was solved by two geometric solution methods. The kinematics solutions was verified by AutoCAD, MATLAB, simulation program was developed using Visual C++.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.1
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• pp.58-66
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• 1992

This paper proposes a neuro-controller for position control of one-link flexible robot arm. Basically the controller consists of a multi-layer neural network and a conventional PD controller. Two controller are parallelly connected. Neural network is traind by the conventional error back propagation learning rules. During learning period, the weights of neural network are adjusted to minimize the position error between the desired hub angle and the actual one. Finally the effectiveness of the proposed approach will be demonstrated by computer simulation.