• Journal of Mechanical Science and Technology
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• v.20 no.7
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• pp.917-928
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• 2006

In recent decades, Artificial Neural Networks (ANNs) have become the focus of considerable attention in many disciplines, including robot control, where they can be used to solve nonlinear control problems. One of these ANNs applications is that of the inverse kinematic problem, which is important in robot path planning. In this paper, a neural network is employed to analyse of inverse kinematics of PUMA 560 type robot. The neural network is designed to find exact kinematics of the robot. The neural network is a feedforward neural network (FNN). The FNN is trained with different types of learning algorithm for designing exact inverse model of the robot. The Unimation PUMA 560 is a robot with six degrees of freedom and rotational joints. Inverse neural network model of the robot is trained with different learning algorithms for finding exact model of the robot. From the simulation results, the proposed neural network has superior performance for modelling complex robot's kinematics.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.792-798
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• 2003

This paper is about implementation of intelligent robot based on home network. Existing robots are mainly stand alone type. Home network is spreading rapidly and can play an important role as a path for informations between appliances in home. Robot can be more intelligent and have versatile functions with a junction of home network. By distribution of tasks through home network, robot doesn't have to process every task. In addition, robot can access to appliances through network as appliances are added continuously. In the future, smart space in which robot behaves on various types of network is in expectation. In this research, home network based system which consists of home server, embedded robot, and intelligent robot is proposed and implemented.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1575-1579
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• 2003

This paper present the control of an intelligent home robot based on home network. The existing research is almost research of independent robot. home network will be a way that equipments in home exchange information. As robot combine home network, robot will be more intelligent and more powerful. We benefit for that load is divided in home network environment. The robot which has ultrasonic sensors performs obstacle avoidance with the Fuzzy Algorithm. Ethernet serial converter transmit the measuring data of home to a home server and the home server accumulates data. The home server controls the robot and manages home according to the acquired data. This paper supposed the home network system that consist of home server, embedded robot and intelligent home robot.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.300-302
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• 2006

Middleware offers function that user application program can transmit data independently of network device. Connection management about network connection of module is important for normal service of module base personal robot. Unpredictable network disconnection is influenced to whole robot performance in module base personal robot. For this, Middleware must be offer two important function. The first is function of error detection and reporting about abnormal network disconnection. Therefore, middleware need method for network error detection and module management to consider special quality that each network device has. The second is the function recovering that makes the regular service possible. When the module closed from connection reconnects, as this service reports connection state of the corresponding module, the personal robot resumes the existing service. In this paper proposed method of network connection management for to support fault tolerant about network error of network module based personal robot.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.779-782
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• 1997

In this paper, accurate position control of a stenciling robot manipulator is designed. The stenciling robot is requried to draw lines and characters on the pavement. Since the robot is huge and heavy, the inertia is expected to play a major role in the tracking performance as desired. Here we are proposing neural network control scheme for a computed-torque like controller for the stenciling robot. On-line compensation is achieved by neural network. Simulation studies with stenciling robot are carried out to test the performance of the proposed control scheme.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.206-212
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• 2010

In this paper, we introduce the concept of robotic zigbee network as a necessary network to provide an application service of robot in the ubiquitous environment and propose an application scenario using the concept of robot Zigbee network. We have performed experiments on the network connection and data transmission which are basic of proposed an application scenario. Through the result of the experiments, we provide basis for development of robot localization and tracking algorithm which minimizes the localization error using robot Zigbee network in the future.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.375-377
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• 2009

This paper researched the algorithm of robot's walking and action on the basis of robot studied and made at our laboratory and studied how to efficiently control the robot joints by developing wireless Digital Servo Motor using Zigbee Sensor Network Module which is using at wide part recently. I realized the stable walking by adopt Press Sensor at the bottom of robot foot to get stability of walking. Also I let the algorithm calculate the robot movement to make the joint motion and monitored the robot walk to its motion. At this Paper, I studied the method organizing the motion by the each robot walking and measuring the torque applying to the joint. And I also knew that it is possible to make its control and construct hardware more conveniently than them of the existing studied and controling 2Legs Walking Robot by applying it at walking robot and developing wireless servo motor by Zirbee Sensor Network.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.831-833
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• 2004

In this paper, an obstacle avoidance algorithm is proposed for a network-based robot considering network delay by distribution. The proposed algorithm is based on the VFH(Vector Field Histogram) algorithm, and for the network-based robot system, in which it is assumed robot localization information is transmitted through network communication. In this paper, target vector for the VFH algorithm is estimated through the robot localization information and the measurement of its delay by distribution. The delay measurement is performed by time-stamp method. To synchronize all local clocks of the nodes distributed on the network, a global clock synchronization method is adopted. With the delay measurement, the robot localization estimation is performed by calculating the kinematics of the robot. The validation of the proposed algorithm is performed through the performance comparison of the obstacle avoidance between the proposed algorithm and the existing VFH algorithm on the network-based autonomous mobile robot.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.217-223
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• 2012

By using the network, the robot can provide the anytime and anywhere various services. There is the advantage that it can provide the real time service by using the network description but the network robot has the network security vulnerability. Therefore, in the network robot environment, the authentication framework which can be satisfied the security function has to be established. In this paper, the security vulnerability which it can be generated in the network robot environment is analyze and the plan for reaction is prepared. And the authentication framework controlling the network robot safely was proposed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1300-1304
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• 2003

The following paper deals with a control problem of a mobile robot in home network environment. The home network causes the mobile robot to communicate with sensors to get the sensor measurements and to be adapted to the environment changes. To get the improved performance of control of a mobile robot in spite of the change in home network environment, we use the fuzzy inference system with multiple reward reinforcement learning. The multiple reward reinforcement learning enables the mobile robot to consider the multiple control objectives and adapt itself to the change in home network environment. Multiple reward fuzzy Q-learning method is proposed for the multiple reward reinforcement learning. Multiple Q-values are considered and max-min optimization is applied to get the improved fuzzy rule. To show the effectiveness of the proposed method, some simulation results are given, which are performed in home network environment, i.e., LAN, wireless LAN, etc.