• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1785-1789
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• 1991

Recently, a number of papers on adaptive control scheme of manipulators are proposed. Slotine and Li[1] showed an adaptive control scheme for robot manipulator. The controller was described in closed form. And later Niemeyer and Slotine discussed about a computational implementation of the controller in recursive form[2]. Walker proposed another adaptive control scheme which can be implemented by a recursive-form controller[4]. Closed-form description is used for the analysis or design of adaptive control systems while recursive-form realization is used for implementation of the controller. The relation between the closed-form realization and the recursive-form one seems to be inadequately referred. Hence, it makes sense to consider the relation between the closed-form description and the recursive-form one. In this paper, first, we make a simple derivation of an closed-form dynamics description of a robot arm from its recursive-form description. And then we derive the closed-form realization of Walker's scheme applied to manipulators having no kinematic loop. We clarify the difference between the Walker's scheme and Slotine's and evaluate the convergence under the controllers.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.111-118
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.4
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• pp.36-42
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• 1998

It is difficult to construct a controller for a mobile robot so that it can adapt appropriately in dynamicallychanging environment. To solve this problem, extensive research has been actively performedto construct a controller by evolutionary method, but few results has come out about the behavioraln~echanism of the evolutionarily constructed controller. This paper attemps to systematically analyze themechanism of the controller constructed by evolution. As a result, we have found that evolution canproduce a controller that can solve a given problem properly, where given problem is divided into severalsub problems and adequate mechanisms emerge for each sub problem. The whole problem hasbeen solved through the complicated interactions of these mechanisms.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.12-20
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• 1998

As an approach to develope a control system with high robustness in changing control environment conditions, this paper will propose a robust control system, using multilayer neural network and biological immune system. The proposed control system adjusts weights of the multilayer neural network(MNN) with the immune algorithm. This algorithm is made up of two major divisions, the innate immune algorithm as a first line of defence and the adaptive immune algorithm as a barrier of self-adjustment. Using the proposed control system based on immune algorithm, we will work out a design for the controller of a robot manipulator. And we will demonstrate the effectiveness of the control system of robot manipulator with computer simulations.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.387-392
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• 2002

This paper presents a new scheme of neural network controller to improve the robustuous of robot manipulator using digital signal processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. During past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Perforating of the proposed controller is illustrated. This paper describes a new approach to the design of adaptive controller and implementation of real-time control for assembling robotic manipulator using digital signal processor. Digital signal processors used in implementing real time adaptive control algorithm are TMS320C50 series made in TI'Co..

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.3
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• pp.54-61
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• 2002

A remote image transmission apparatus combines robot technology and image transmission there is safe problem or place that a person can not go. Recently, control apparatus that use wire and RF between web server and robot for remote control are developed. But there is problem that must install internet line and communication distance. Transmission distance problem call solve when using the equipment of RF, but price of RF router is problem that is very high cost. In this paper, we developed remote control system using the CDMA cellular phone communication network that can control image transmission and image transmission apparatus to solve these problem. Developed system could solve defects of methods that use existent RF and internet. And could transmit the most suitable image and voice under limited condition include current communication network.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1039-1044
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• 2005

This paper presents a robotic agent design and application in the ubiquitous intelligent space. We set up an experimental environment with Bluetooth host, Bluetooth client, furniture and home appliance, and robotic agents. First, the agents basically performed patrol guard to detect unexpected penetration, and to keep home safely from gas-leakage, electric leakage, and so on. They were out to patrol fur a robbery while navigating in a living room and a private room. In this task, we used an area-based action making and a hexagon-based Q-learning to control the agents. Second, the agents communicate with Bluetooth host device to access and control a home appliance. The Bluetooth host offers a manual control to person by inquiring a client robot when one would like to check some place especially. In this exercise, we organize asynchronous connection less (ACL) between the host and the client robots and control the robot maneuver by Bluetooth host controller interface (HCI).

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.134-139
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• 2001

This paper presents a new scheme of neural network controller to improve the robustuous of robot manipulator using digital signal processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. During past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Perforating of the proposed controller is illustrated. This paper describes a new approach to the design of adaptive controller and implementation of real-time control for assembling robotic manipulator using digital signal processor. Digital signal processors used in implementing real time adaptive control algorithm are TMS320C50 series made in TI'Co..

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.50-57
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• 2005

We present a simple and effective method of face and facial feature detection under pose variation of user face in complex background for the human-robot interaction. Our approach is a flexible method that can be performed in both color and gray facial image and is also feasible for detecting facial features in quasi real-time. Based on the characteristics of the intensity of neighborhood area of facial features, new directional template for facial feature is defined. From applying this template to input facial image, novel edge-like blob map (EBM) with multiple intensity strengths is constructed. Regardless of color information of input image, using this map and conditions for facial characteristics, we show that the locations of face and its features - i.e., two eyes and a mouth-can be successfully estimated. Without the information of facial area boundary, final candidate face region is determined by both obtained locations of facial features and weighted correlation values with standard facial templates. Experimental results from many color images and well-known gray level face database images authorize the usefulness of proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.93-101
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• 2011

For mobile robot, recognizing its current location is very important to navigate autonomously. Especially, loop closing detection that robot recognize location where it has visited before is a kernel problem to solve localization. A considerable amount of research has been conducted on loop closing detection and localization based on appearance because vision sensor has an advantage in terms of costs and various approaching methods to solve this problem. In case of scenes that consist of repeated structures like in corridors, perceptual aliasing in which, the two different locations are recognized as the same, occurs frequently. In this paper, we propose an improved method to recognize location in the scenes which have similar structures. We extracted salient regions from images using visual attention model and calculated weights using distinctive features in the salient region. It makes possible to emphasize unique features in the scene to classify similar-looking locations. In the results of corridor recognition experiments, proposed method showed improved recognition performance. It shows 78.2% in the accuracy of single floor corridor recognition and 71.5% for multi floor corridors recognition.