• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.807-810
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• 1997

Digital control of robot manipulator employs discrete-time robot models. It is important to explore effective discrete-time robot models and to analyze their properties in control system designs. This paper presents a new type discrete-time robot model. The model is derived by using trapezoid rule to approximate the convolution integral term, then eliminating nonlinear force terms from robot dynamical equations. The new model obtained has very simple structure, and owns the properties of independence to the nonlinear force terms. According to evaluation criteria, three aspects of the model properties: model accuracy, model validity range and model simplicity are examined and compared with commonly used discrete-time robot models. The validity of the proposed model and its advantages to control system designs are verified by simulation results.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1825_1826
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• 2009

This paper is proposed to make a virtual reality 3D operation model including a robot model and an environment model for a robot contest. First of all, we make the robot model using Open Dynamics Engine(ODE), and the environment model similar to the robot contest. These ODE models are programmed by the C-language. Lastly, we perform simulations to verify the robot model and the environment model. As a result, it shows the possibility of models for the robot contest.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.856-861
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• 2011

The mobile robot controller is designed to track the target and to maintain the formation at the same time. Formation control is included in mobile robot controller by extending the trajectory tracking algorithm. The dynamic model of mobile robot is used with kinematic model considering the practical physical parameters of mobile robot. The dynamic model of mobile robot transforms velocity control input of kinematic model into torque control input which is the practical control input of mobile robot. Formation controller of mobile robot is designed to satisfy Lyapunov stability by backstepping method. The designed formation controller is applied to the mobile robot for various target movements and simulated to confirm the Lyapunov stability.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.593-599
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• 1999

A mobile robot in FMS environment should be able to nevigate itself. Therefore, path planning is necessary for the mobile robot to perform its tasks without being lost. Path planning using a network model gives oprimal paths to every pair of nodes but building this model demands accurate information of environments. In this paper, a method to build a network model using sonar sensors is presented. The main idea is to build a quad tree model by using sonar sensors and convert the model to a network model for path planning. The new method has been implemented on a mobile robot. Experimental results show that the mobile robot constructs an accurate network model using inaccurate sonar data.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.64-71
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• 1997

Objective of calibration is to find out the accurate kinematic relationships between robot joint angles and the position of the end-effector by estimating accurate model parameters defining the kinematic function. Estimating the model parameters requires measurement of the end-effector position at a number of different robot configurations. This paper studies the implication of measurement configurations in robot calibration. For selecting appropriate measurement configurations in robot calibration, an index is defined to measure the observability of the model parameters with respect to a set of robot configurations. It is found that, as the observability index of the selected measurement configurations increase the attribution of the position errors to the parameter errors becomes dominant while the effects of the measurement and unmodeled errors are less significant; consequently better estimation of parameter errors is expected. To demonstrate the implication of the observability measure in robot calibration, computer simulations are performed and their results are discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1025-1030
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• 2005

This paper deals with the emotional model of the software-robot. The software-robot requires several capabilities such as sensing, perceiving, acting, communicating, and surviving. and so on. There are already many studies about the emotional model like KISMET and AIBO. The new emotional model using the modified friendship scheme is proposed in this paper. Quite often, the available emotional models have time invariant human respond architectures. Conventional emotional models make the sociable robot get around with humans, and obey human commands during robot operation. This behavior makes the robot very different from real pets. Similar to real pets, the proposed emotional model with the modified friendship capability has time varying property depending on interaction between human and robot.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.2
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• pp.125-130
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• 2016

In this paper, we deal with the dynamic walking of a humanoid robot. In our method, the inverted pendulum model is used as a dynamic model for a humanoid robot in which the Zero Moment Point (ZMP) and COG constraints of the robot are analyzed by considering the motion of the robot as that of an inverted pendulum. The motion of a humanoid robot should be generated by considering the dynamics of the robot, which commonly requires a large amount of computation. If a robot walks from one position to another while keeping the ZMP in the stable region, then the robot remains dynamically stable. The linear inverted pendulum model regards the whole robot as a point mass. It is simple, and relatively less computation is needed; however, it cannot model the whole dynamics of a humanoid robot. We propose a method for modeling a humanoid robot as an inverted pendulum system having 14 point masses. We also show that the dynamic stability of a humanoid robot can be determined more precisely by our method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.152-159
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• 2005

This paper describes the application of a model-based system design method critical to complex intelligent systems, PSARE, to a welding robot development to define its top level architecture. The PSARE model consists of requirement model which describes the core processes(function) of the system, enhanced requirement model which adds technology specific processes to requirement model and allocates them to architecture model, and architecture model which describes the structure and interfaces and flows of the modules of the system. This paper focuses on the detailed procedure and method rather than the detailed domain model of the welding robot. In this study, only the top level architecture of a welding robot was defined using the PSARE method. However, the method can be repeatedly applied to the lower level architecture of the robot until the process which the robot should perform can be clearly defined. The enhanced data flow diagram in this model separates technology independent processes and technology specific processes. This approach will provide a useful base not only for improvement of a class of welding robots but also for development of increasingly complex intelligent real-time systems.

• 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 Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.221-224
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• 2005

This paper proposes the system model that is more efficient and active than formal home automation system and it can conquer the limits of formal one using intelligent mobile robot. This system uses specialized intelligent mobile robot for home environment and the robot moves around home instead of human. We call the system model to HAuPIRS (Home Automation system using PDA based Intelligent Robot System). HAuPIRS control architecture is composed three parts and each part is User Level, Cognitive Level, Executive Level. It is easy to use system and possible to extend the home apparatusfrom new technology. We made the PBMoRo System (PDA Based Mobile Robot System) based on HAuPIRS architecture and verified the efficiency of the system model.