• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.123-129
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• 2001

Recent requirements for the fast and accurate motion in industrial robot manipulators need more advanced control tech-niques. To satisfy the requirements, importance of force control is being continuously increased and the expensive force sensor is usually installed to obtain the contact force information in practice. This information is indispensable for the force control of maintaining the desired contact force. However, the sensor cost is too high to be used in industrial applications. In this paper, it is proposed to estimated the contact force occurring between the end-effector of 2 DOF robots and environ-ment. The contact force estimation system is developed based on the static and dynamic models of 2 DOF robot manipula-tors. where the contact force is described with respect to the link torque. The Extended Kalman Filter is designed and its performance is verified in simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.766-771
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• 1992

The hydrodynamic coefficients estimation problem is important to develop an underwater vehicle and design a controller for it. In this paper, an identification theory, the Extended Kalman Filter, is applied to this parameter estimation problem. In the case that a process noise is not used, all of the parameters are almost exactly converged to the true values respectively. When a process noise is used, all of the parameters are converged to the true values, too, although some parameter estimates are slightly biased. The comparisons of the two trajectories between those generated by the true parameters and those by the estimated parameters show that the parameter estimation problem is well-solved.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.904-908
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• 2008

Every autonomous system like a robot needs a power source known as a battery. And proper management of the battery is very important for proper operation. To know State of Charge(SOC) of a battery is the very core of proper battery management. In this paper, the SOC estimation problem is tackled based on the well known Extended Kalman Filter(EKF). Combined the existing battery model is used and then EKF is employed to estimate the SOC. SOC table is constructed by extensive experiment under various conditions and used as a true SOC. To verify the estimation result, extensive experiment is performed with various loads. The comparison result shows the battery estimation problem can be well solved with the technique proposed in this paper. The result of this paper can be used to develop related autonomous system.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.4 s.23
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• pp.14-23
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• 2005

In this paper we propose a sensor fusion method for the navigation algorithm which can be used to estimate state vectors such as position and velocity for its motion control using multi-sensor output measurements. The output measurement we will use in estimating the state is a series of known multi-sensor asynchronous outputs with measurement noise. This paper investigates the Extended Kalman Filtering method to merge asynchronous heading, heading rate, velocity of DVL, and SSBL information to produce a single state vector. Different complexity of Kalman Filter, with. biases and measurement noise, are investigated with theoretically data from MOERI's SAUV. All levels of complexity of the Kalman Filters are shown to be much more close and smooth to real trajectories then the basic underwater acoustic navigation system commonly used aboard underwater vehicle.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.5
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• pp.455-462
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• 2009

This paper presents design concepts of a reconfigurable mobile robot for both of indoor and outdoor applications. A linkage mechanism and wheel-in-motors give the proposed mobile robot various driving modes in maneuver and good adaptability to irregular surface. Since the mobile robot receives multiple sensor signals from odometers and an orientation sensor, states related to the position and the orientation of the mobile robot are optimally estimated by an extended Kalman filter. Simulations and experimental results show that the performance of dead reckoning on estimating the pose of a mobile robot can be improved remarkably by the optimal state observer.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.182-188
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• 2011

This paper describes a method of road tracking by using a vision and laser with extracting road boundary (road lane and curb) for navigation of intelligent transport robot in structured road environments. Road boundary information plays a major role in developing such intelligent robot. For global navigation, we use a global positioning system achieved by means of a global planner and local navigation accomplished with recognizing road lane and curb which is road boundary on the road and estimating the location of lane and curb from the current robot with EKF(Extended Kalman Filter) algorithm in the road assumed that it has prior information. The complete system has been tested on the electronic vehicles which is equipped with cameras, lasers, GPS. Experimental results are presented to demonstrate the effectiveness of the combined laser and vision system by our approach for detecting the curb of road and lane boundary detection.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.14-19
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• 2000

Recent requirements for the fast and accurate motion in industrial robot manipulator need more advanced control techniques. To satisfy the requirements, importance of the force control is being continuously increased and the expensive force sensor is usually installed to obtain the contact force information in practice. This information is indispensable for the force control of maintaining the desired contact force. However the sensor cost is too high to be used in industrial applications. In this paper, it is proposed to estimate the contact force occurred between the end-effector of 2 DOF robots and environment. The contact force estimation system is developed based on the static and dynamic models of 2 DOF robot manipulators, where the contact force is described with respect to the link torque. The Extended Kalman Filter is designed and its performance is verified in simulations.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.2
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• pp.33-39
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• 2013

Multilateration(MLAT) may complement secondary surveillance radar and also act as a real-time backup for the ADS-B system. This System is using time difference of arrival (TDOA) and based on triangulation principle. Each TDOA measurement defines a hyperbola describing possible aircraft locations. The accuracy in MLAT system depends on the positional relationship of the receiver and aircraft. There are various algorithms to localize aircraft based on TOA estimation. In this paper, we use least square method and extended Kalman filter and compare their results. Study results show that the extend Kalman filter provides a better performance than the least square method.

• Transactions of The Korea Fluid Power Systems Society
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• v.1 no.4
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• pp.9-14
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• 2004

An estimation technique called the Extended Kalman filter is used to estimate viscous friction, spring initial contraction, and the spring constant on the swash plate of a variable displacement pump. The feasibility of the approach was established using a simulation study. It showed that these parameters could be estimated very accurately in a reliable and independent fashion. A special experimental system was set up to facilitate the measurement of certain states to enhance the Kalman Filtering approach. The aforementioned parameters were estimated and found to be reasonably repeatable for a common operating point. It was very evident that as the operating conditions changed (i.e. temperature) so did the estimated values of certain parameters such as viscous friction. This was believed to be a good verification test for the approach.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.2 s.17
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• pp.22-31
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• 2004

In this paper, the measurements preprocessing algorithm for the fading of bearing and frequency measurements is proposed, which can improve the performance of BFTMA(Bearing and Frequency Target Motion Analysis). The fading and detection relation between bearing and frequency are rigorously established for measurements preprocessing, and BFTMA can be carried out the estimation of target motion by using measurements preprocessing. Batch estimation with bearing and frequency using the proposed algorithm can be applied to estimate the initial target states despite of the fading of frequency measurement. Simulation results show that BFTMA using the proposed measurements preprocessing has superior estimation performance, compared with batch estimation using only bearing measurements.