• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1587-1592
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• 2003

There are three kinds of singularity in controlling redundant manipulators. Kinematic, algorithmic and representation singularities are those. If manipulators fall into any singularity without proper action to avoid it, the control system must go away from our desire, and we can meet a dangerous situation. Hence, we have to deal the singularities very carefully. In this paper, we describe an on-line solution for avoiding the occurrence of both algorithmic and kinematic singularities in task-priority based kinematic controllers of robotic manipulators. Representation singularity can be easily avoided by using proper representation algorithm, so, in this paper, we only consider kinematic and algorithmic singularities. The proposed approach uses a desired task reconstruction and a successive task projection in order to maintain the measure for singularity over a user defined minimum value. It shows a gain in performance and a better task error especially when working in proximity of singular configurations. It is particularly suitable for autonomous systems where an off-line trajectory control scheme is often not applicable. The advantage and performance of the proposed controller is verified by simulation works. And, the experiment with real manipulator is remaining for the future works.

• Journal of Drive and Control
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• v.14 no.4
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• pp.51-60
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• 2017

In this study to develop disaster response robot in complex disaster site, we present the design of hydraulic manipulators for armored robot systems. To this end, we performed voice of customer researches with firefighters and rescue personnel. We created and analyzed the mission scenario of firefighters and rescue personnel in complex disaster situations, and derived the required functions of the robot to successfully perform missions. A heavy-duty, heat resistant, dexterous hydraulic robot manipulators is designed to realize the required functions. The designed robot has been verified through simulations and analysis in terms of the working area of the robot, actuating torques, and temperature analysis.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.96-101
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• 2007

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is e. kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.731-737
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• 2013

In this paper, we propose an image-based output feedback robust controller of robot manipulators which have bounded parametric uncertainty. The proposed controller contains an integral action and high-gain observer in order to improve steady state error of joint position and performance deterioration due to measurement errors of joint velocity. The stability of the closed-loop system is proved by Lyapunov approach. The performance of the proposed method is demonstrated by simulations on a 5-link robot manipulators with two degrees of freedom.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.123-128
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• 1996

Kinematically redundant manipulators have been studied because of its usefulness of kinematic redundancy. It is natural that the kinematic redundancy induces a kind of control redundancy. By using the weighted kinematically decoupled joint space decomposition, we unify the control redundancy and the kinematic redundancy parameterized by the joint space weighting matrix. Concentrating to the particular component of each decomposition, we can describe the local minimization behavior of the control weighted quadratic by each weighted decomposition. The result extends the conventional results on general setting, and should be of interest in understanding the motion behavior of kinematically redundant manipulators.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.524-529
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• 2005

In this paper, a novel neural network compensation technique for PD like fuzzy controlled robot manipulators is presented. A standard PD-like fuzzy controller is designed and used as a main controller for controlling robot manipulators. A neural network controller is added to the reference trajectories to modify input error space so that the system is robust to any change in system parameter variations. It forms a neural-fuzzy control structure and used to compensate for nonlinear effects. The ultimate goal is same as that of the neuro-fuzzy control structure, but this proposed technique modifies the input error not the fuzzy rules. The proposed scheme is tested to control the position of the 3 degrees-of-freedom rotary robot manipulator. Performances are compared with that of other neural network control structure known as the feedback error learning structure that compensates at the control input level.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1160-1166
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• 2015

This paper proposes a decentralized robust adaptive control scheme for robot manipulators with input torque saturation in the presence of uncertainties. The control system should consider the practical problems that the controller gain coefficients of each joint may be nonlinear time-varying and the input torques applied at each joint are saturated. The proposed robot controller overcomes the various uncertainties and the input saturation problem. The proposed controller is comparatively simple and has no robot model parameters. The proposed controller is adjusted by the adaptation laws and the stability of the control system is guaranteed by the Lyapunov function analysis. Simulation results show the validity and robustness of the proposed control scheme.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2911-2914
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• 2003

Conventionally, biological manipulations have been performed manually with long training and pretty low success rates. To overcome this problem, a novel biological manipulation system has been developed to manipulate biological cells without any interference of a human operator, In this paper, we demonstrate a development of tole-autonomous Cell Manipulation System (CMS) using an image processing at a remote site. The CMS consists of two manipulators, a plane stage, and an optical microscope. We developed deformable template-model-matching algorithm for micro objects and pattern matching algorithm of end effect for these manipulators in order to control manipulators and the stage. Through manipulation of biological cells using these algorithms, the performance of the CMS is verified experimentally.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.486-490
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• 1993

In addtion to a basic motion task, redundant manipulators can achieve some additional tasks by optimizing proper performance criteria. Some of performance criteria can be transformed to inequality constraints. So the redundancy resolving problem can be reformulated as a local optimization problem with equality constraints for the end effector and inequality constraints for some performance criteria. In this article, we propose a method for solving the inverse kinematics of a manipulator with redundancy using the Kuhn-Tucker theorem to incorporate inequality constraints. With proper choice of inequality constraints, the proposed method gives a way of optimizing multiple criteria in redundant manipulators.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.2
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• pp.467-475
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• 1998

The Six Degree-of-Freedom manipulators are generally operated by linear actuators which are hydraulic cylinder, pneumatic cylinder, ball-screw. But these actuators are not adequate to have a wide work-space, and furthermore some of them have a self-locking property. Therfore, we have designed a new manipulator which fully overcomes these demerits. The new manipulating system consists of 6 DC-motors to generate operation forces and 6 position transducers to feedback displacement signals. This paper presents an overview of the design and characteristics of 6 Degree-of-Freedom force feedback manipulators for vitual reality implementation. we can operate Six Degree-of-Freedom manipulator with six motors and six potentiometers.