• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.3
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• pp.401-407
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• 2019

In this paper, the position estimation considering wheel slip of mecanum wheeled mobile robots is discussed. Since the mecanum wheeled mobile robot does not need a space to rotate, it is very suitable in narrow industrial fields. However, the slip caused by the roller attached to the wheel makes it difficult to estimate the position precisely. Due to these limitations, mecanum wheels are rarely applied to unmanned mobile robots in automation factories. In this paper, a method to compensate the orientation and distance error caused by the slip is proposed. The exact orientation is measured by fusing gyro and magnetometer sensor data with application of Kalman filter. In addition, the kinematic model accounting slip effects will be defined to compensate the distance error.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.1
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• pp.119-126
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• 2000

In constructing the positioning system based on a conventional dead-reckoning for a wheeled vehicle with pneumatic tires, the position estimation error is inevitable as changes of the radius of the wheels depend on live load and variable enviroment. Therefore, this paper proposes the positioning system which can estimate the error source i.e. the vehicle parameter errors, such as the right and left wheel radius error, using gyroscope and ultrasonic sensor and correct the parameter to reduce the dead-reckoned position estimation error. The extended Kalman filter was used as a method for the multisensor data fusion. The simulation to verify the effectiveness of the proposed positioning system is performed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.11
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• pp.1645-1650
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• 2015

This paper presents the 3-dimensional electromagnetic field analysis method and correction of sensor distortion that is used by a motor speed sensor. The magnetic sensors are being expanded due to lower price than the other speed sensors such as resolver and encoder. Magnetic sensor generates sine and cosine waves when the motor rotates. However, the sine and cosine signals are distorted due to magnetic noise, which makes the angle error of the sensor, generated near by the Hall element. This paper defines an optimal design variables by using the Taguchi method to minimize output distortion of the magnetic sensor and permanent magnet. To enhance reliability of the magnetic position sensor from sensitivity error, assembly amplitude mismatch and the electrical angle, 3-Dimensional electromagnetic finite element method and correction algorithm errors were performed in due of the magnetic sensor in order to improve the quality of the initial production model.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.187-192
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• 1992

There are several potential error sources that can affect the estimation of the position of an object using combined vision and acceleration measurements. Two of the major sources, accelerometer dynamics and random noise in both sensor outputs, are considered. Using a second-order model, the errors introduced by the accelerometer dynamics are reduced by the smaller value of damping ratio and larger value of natural frequency. A Kalman filter approach was developed to minimize the influence of random errors on the position estimate. Experimental results for the end-point movement of a flexible beam confirmed the efficacy of the Kalman filter algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.3
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• pp.51-58
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• 2004

This paper describes the development of a small 6-axis force/moment sensor for robot's finger, which measures farces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously. In order to safely grasp an unknown object using the robot's gripper, and accurately perceive the position of it in the gripper, it should measure the force in the gripping direction, the force in the gravity direction and the moments each direction, and perform the force control using the measured forces and moments. Also, it should detect the moments Mx (x-direction moment), My and Mz to accurately perceive the position of the object in the grippers. Thus, the robot's gripper should be composed of 6-axis force/moment sensor that can measure forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously. In this paper, the small 6-axis force/moment sensor for measuring forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously was newly modeled using several parallel-plate beams, designed, and fabricated. The characteristic test for the developed sensor was performed, and the result shows that intereference errors of the developed sensor are less than 4.23％. Thus, the developed small 6-axis force/moment sensor may be used a robot's gripper.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.103-114
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• 2024

The escalating demands for high-resolution satellite imagery necessitate the dissemination of geospatial data with superior accuracy.Achieving precise positioning is imperative for mitigating geometric distortions inherent in high-resolution satellite imagery. However, maintaining sub-pixel level accuracy poses significant challenges within the current technological landscape. This research introduces an approach wherein upsampling is employed on both the satellite image and ground control points (GCPs) chip, facilitating the establishment of a high-resolution satellite image precision sensor orientation. The ensuing analysis entails a comprehensive comparison of matching performance. To evaluate the proposed methodology, the Compact Advanced Satellite 500-1 (CAS500-1), boasting a resolution of 0.5 m, serves as the high-resolution satellite image. Correspondingly, GCP chips with resolutions of 0.25 m and 0.5 m are utilized for the South Korean and North Korean regions, respectively. Results from the experiment reveal that concurrent upsampling of satellite imagery and GCP chips enhances matching performance by up to 50% in comparison to the original resolution. Furthermore, the position error only improved with 2x upsampling. However,with 3x upsampling, the position error tended to increase. This study affirms that meticulous upsampling of high-resolution satellite imagery and GCP chips can yield sub-pixel-level positioning accuracy, thereby advancing the state-of-the-art in the field.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.574-592
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• 2016

Range-free localization algorithm computes a normal node's position by estimating the distance to anchors which know their actual position. In recent years, reliable anchor selection research has been gained a lot of attention because this approach improves localization accuracy by selecting the only subset of anchors called reliable anchor. The distance estimation accuracy and the geometric shape formed by anchors are the two important factors which need to be considered when selecting the reliable anchors. In this paper, we study the relationship between a relative position of three anchors and localization error. From this study, under ideal condition, which is with zero localization error, we find two conditions for anchor selection, thereby proposing a novel anchor selection algorithm that selects three anchors matched most closely to the two conditions, and the validities of the conditions are proved using two theorems. By further employing the conditions, we finally propose a novel range-free localization algorithm. Simulation results show that the proposed algorithm shows considerably improved performance as compared to other existing works.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.797-800
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• 1992

Much experience and knowledge is needed in welding because there are many working parameters and quantitative description is difficult. Therefore, introduction of expert system based on such data base has been required. In this study, welding heat and shape of bead was controlled by fuzzy inference with the welding condition, position error and voltage and current error of robot. For this, torch trajectory of robot was generated by modeling the working data with CAD and then welding was carried out through down loading to robot. And working error was controlled by on-line communication.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.2
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• pp.189-196
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• 2019

The inertial sensor errors in SDINS(Strapdown Inertial Navigation System) can be compensated by rotating the inertial measurement unit and it is called RINS(Rotational Inertial Navigation System). It is assumed that the error of the inertial sensor in RINS is a static bias. However, the error of the inertial sensor actually developed and produced is not a static bias due to the change of the temperature applied to the sensor and the influence of the earth's gravity acceleration. In this paper, we propose a six-position gyro bias calibration method to evaluate the gyro bias required for RINS and present the test results of applying it to a ring laser gyro inertial navigation system under development.

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.28-36
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• 2006

In this paper, an algorithm to classify the 4 motions of arm and a control system to position control the prosthesis are studied. To classify the 4 motions, we use flex sensors which is electrical resistance type sensor that can measure warp of muscle. The flex sensors are attached to the biceps brchii muscle and coracobrachialis muscle and the sensor signals are passed the sensing system. 4 motion of the forearm - flexion and extension, the pronation and supination are classified from this. Also position of forearm is measured from the classified signals. Finally, A two D.O.F prosthesis arm with RC servo-motor is designed to verify the validity of the algorithm. At this time, fuzzy controller is used to reduce the position error by rotary inertia and noise. From the experiment, the position error had occurred within about 5 degree.