• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.77-86
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• 2006

A new method in robot path generation is presented using an analysis of the characteristics of multi-robot collision avoidance. The research is based on the concept of the collision map, where the collision between two robots is presented by a collision region and a crossing curve TLVSTC (traveled length versus servo time curve). Analytic collision avoidance is considered by translating the collision region in the collision map. The 4 different translations of collision regions correspond to the 4 parallel movements of the actual original robot path in the real world. This analysis is applied to path modifications where the analysis of collision characteristics is crucial and the resultant path for collision avoidance is generated. Also, the correlations between the translations of the collision region and robot paths are clarified by analyzing the collision/non-collision areas. The influence of the changes of robot velocity is investigated analytically in view of collision avoidance as an example.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1201-1207
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• 2010

This paper shows to stabilize a balancing robot. We derive the dynamics of a balancing robot and design its controller using LQR method. For stabilizing balancing robot, we introduce a method to detect an angle using inertial sensors. In this study, we use a complementary filter to fuse signals by frequency response of gyroscope and accelerometer in order to measure the inclined angle of balancing robot. The filter coefficients are obtained by least square to minimize error in angle-detecting filter design. And then, after we derive a dynamics of balancing robot using Lagrange method, we linearize that dynamics for using LQR method.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.37-42
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• 2006

Recently, studying on modeling the emotion of a robot has become issued among fields of a humanoid robot and an interaction of human and robot. Especially, modeling of the motivation, the emotion, the behavior. and so on, in the robot, is hard and need to make efforts to use ow originality. In this paper, new modeling using mathematical formulations to represent the emotion and the behavior selection is proposed for the software robot with virtual sensor modules. Various points which affect six emotional states such as happy or sad are formulated as simple exponential equations with various parameters. There are several experiments with seven external sensor inputs from virtual environment and human to evaluate this modeling.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.969-972
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• 1988

A conventional robotic manipulator is usually a very complicated system whose dynamics is too computationally time consuming for dynamic analysis and real time control. The authors have proposed the general design criteria of the robot links which greatly simplify the robot dynamic characteristics. In this paper these design guidelines are applied to a 6 degree of freedom PUMA 560 robot in order to realize actual implementation of the design concept. Based upon the design concept, the dynamic equations of the redesigned robot were derived. Dynamic characteristics of two systems, the ideally designed and conventional robot, are compared with respect to the joint input torque characteristics and degree of the coupling between the robot joints.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.728-733
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• 2009

This paper presents the compensation of mechanical deflection error in SCARA robot. End of robot gripper is deflected by weight of arm and pay-load. If end of robot gripper is deflected constantly regardless of robot configuration, it is not necessary to consider above mechanical deflection error. However, deflection in end of gripper varies because that moment of each axis varies when robot moves, it affects the relative accuracy. I propose the compensation method of deflection error using neural network. FEM analysis to obtain the deflection of gripper end was carried out on various joint angle, the results is used in neural network teaming. The result by simulation showed that maximum relative accuracy reduced maximum 9.48% on a given working area.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.406-410
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• 2008

This paper presents a new robot calibration algorithm with joint stiffness parameters for the enhanced positioning accuracy of industrial robot manipulators. This work is towards on-going development of an industrial robot calibration software which is able to identify both the kinematic and non-kinematic robot parameters. In this paper, the conventional kinematic calibration and its important considerations are briefly described first. Then, a new robot calibration algorithm which simultaneously identifies both the kinematic and joint stiffness parameters is presented and explained through a computer simulation with a 2 DOF manipulator. Finally, the developed algorithm is implemented to Hyundai HX165 robot and its resulting improvement of the positioning accuracy is addressed.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.551-558
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• 2008

This paper deals with the real-time stable walking for a humanoid robot, ISHURO-II, on uneven terrain. A humanoid robot necessitates achieving posture stabilization since it has basic problems such as structural instability. In this paper, a stabilization algorithm is proposed using the ground reaction forces, which are measured using FSR (Force Sensing Resistor) sensors during walking, and the ground conditions are estimated from these data. From this information the robot selects the proper motion pattern and overcomes ground irregularities effectively. In order to generate the proper reaction under the various ground situations, a fuzzy algorithm is applied in finding the proper angle of the joint. The performance of the proposed algorithm is verified by simulation and walking experiments on a 24-DOFs humanoid robot, ISHURO-II.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.41-48
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• 2014

This paper analyzes the Monte Carlo localization (MCL) method, which estimates the pose of an indoor mobile robot. A mobile robot must know where it is to navigate in an indoor environment. The MCL technique is one of the most influential and popular techniques for estimation of robot position and orientation using a particle filter. For the analysis, we perform experiments in an indoor environment with a differential drive robot and ultrasonic range sensor system. The analysis uses MATLAB for implementation of the MCL and investigates the effects of the control parameters on the MCL performance. The control parameters are the uncertainty of the motion model of the mobile robot and the noise level of the measurement model of the range sensor.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.246-252
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• 2005

Intelligent Space is a space where many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents, which provide human with services. To realize this, human and mobile robots have to approach each other as much as possible. Moreover, it is necessary for them to perform interactions naturally. It is desirable for a mobile robot to carry out human affinitive movement. In this research, a mobile robot is controlled by the Intelligent Space through its resources. The mobile robot is controlled to follow walking human as stably and precisely as possible. In order to follow a human, control law is derived from the assumption that a human and a mobile robot are connected with a virtual spring model. Input velocity to a mobile robot is generated on the basis of the elastic force from the virtual spring in this model. And its performance is verified by the computer simulation and the experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.322-329
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• 2005

This paper considers the application of mobile robot to the herding problem. The herding problem involves a ‘pursuer’ trying to herd a moving ‘evader’ to a predefined location. In this paper, two mobile robots act as pursuer and evader in the fenced area, where the pursuer robot uses a fuzzy cooperative decision strategy (FCDS) in the herding algorithm. To herd evader robot to a predefined position, the pursuer robot calculates strategic herding point and then navigates to that point using FCDS. FCDS consists of a two-level hierarchy: low level motion descriptors and a high level coordinator. In order to optimize the FCDS, we use the multi­thread evolutionary programming algorithm. The proposed algorithm is implemented in the real mobile robot system and its performance is demonstrated using experimental results.