• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.734-739
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• 2003

A new method of estimating the pose of a mobile-task robot is developed based upon an active calibration scheme. The utility of a mobile-task robot is widely recognized, which is formed by the serial connection of a mobile robot and a task robot. For the control of the mobile robot, an absolute position sensor is necessary. This paper proposes an active calibration scheme to estimate the pose of a mobile robot that carries a task robot on the top. The active calibration scheme is to estimate a pose of the mobile robot using the relative position/orientation to a known object whose location, size, and shape are known a priori. Through the homogeneous transformation, the absolute position/orientation of the camera is calculated and that is propagated to getting the pose of a mobile robot. With the experiments in the corridor, the proposed active calibration scheme is verified experimentally.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2365-2370
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• 2017

In this paper, we propose a motion and position recognition technique considering an experiential VR environment. Motion recognition attaches a plurality of AHRS devices to a body part and defines a coordinate system based on this. Based on the 9 axis motion information measured from each AHRS device, the user's motion is recognized and the motion angle is corrected by extracting the joint angle between the body segments. The location recognition extracts the walking information from the inertial sensor of the AHRS device, recognizes the relative position, and corrects the cumulative error using the BLE fingerprint. To realize the proposed motion and position recognition technique, AHRS-based position recognition and joint angle extraction test were performed. The average error of the position recognition test was 0.25m and the average error of the joint angle extraction test was $3.2^{\circ}$.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.228-235
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• 2007

The main purpose of this paper is to manage the container property effectively at the container yard by applying the RTLS technology to the field of port logistics. Yet, many kinds of noises happen to be inputted with the distance value(between the reader and the tag) which is to be inputted into the location identification algorithm, which makes the distance value jumped due to the system noise of the ultrasonic sensor module and the measurement noise. The Kalman Filter is widely used to prevent this jump occurrence; the noises are eliminated by using the EKF(Extended Kalman Filter) while considering that the distance information of the ultrasonic sensor is non-linear. Also, the 3D RTLS system at the port container yard suggested in this research is designed not to be interrupted for its ultrasonic transmission by positioning the antenna at the front of each sector of the container where the active tags are installed. We positioned the readers, which function as antennas for location identification, to four places randomly in the absolute coordinate and let the positions of the active tags identified by using the distance data delivered from the active tags. For the location identification algorithm used in this paper, the triangulation measurement that is most used in general is applied and newly reorganized to calculate the position of the container. In the first experiment, we dealt with the error resulting in the angle and the distance of the ultrasonic sensor module, which is the most important in the hardware performance; in the second, we evaluated the performance of the location identification algorithm, which is the most important in the software performance, and tested the noise cancellation effects for the EKF. According to the experiment result, the ultrasonic sensor showed an average of 3 to 5cm error up to $45^{\circ}$ in case of $60^{\circ}$ or more, non-reliable linear distances were obtained. In addition, the evaluation of the algorithm performance showed an average of $4^{\circ}{\sim}5^{\circ}$ error due to the error of the linear distance-this error is negligible for most container location identifications. Lastly, the experiment results of noise cancellation and jump preservation by using the EKF showed that noises were removed in the distance information which was entered from the input of the ultrasonic sensor and as a result, only signal was extracted; thus, jumps were able to be removed and the exact distance information between the ultrasonic sensors could be obtained.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.5
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• pp.20-25
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• 2011

In this paper, we reviewed the spindle system's motor and bearing and its mode safety for optimal design of a high speed spindle system that exceeds DmN value of 1,500,000. We could verify that it has a separation margin during critical speed by performing critical speed analysis. Also, we have selected an optimal sensoring installation location and actually manufactured & installed the sensor by identifying the stress concentration position in the axial load through finite element analysis to install the built-in piezo electric type load sensor to the spindle housing that can measure and monitor the machining load during high speed rotation of the spindle. Reproducibility is also verified by calibrating the error through the sensor's sensitivity adjustment after comparing the output between the plate dynamoneters and the load sensor to confirm the reproducibility of the load sensor.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.11
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• pp.2902-2912
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• 1994

The ultrasonic array sensor system, consisting of one transmitter and fourreceivers instead of the traditional combination of a transmitter and a receiver is proposed in order to identify the location of objects. From the theoretical analysis and the experimental results, it is found that this new array sensor system could derive the information on the position of objects accurately, while the traditional sensor system could provide only the informatioin on the distance to objects. This sensor system is used to develop a sonar-based local mapping algorithm. The local map is used to find the existence of possible gates, through which the mobile robots can pass, and to select the suitable one in order for the robots to reach the goal safely in the presence of obstacles. The performance of the proposed local map algorithm is demonstrated experimentally in a small working area with several obstacles. It is found that the quality of the resulting local map is sufficient for the avoidance of collisions between the robots and obstacles and for the selection of the suitable gate leading to the goal. It is also shown that the global map of the working area could be obtained by integrating several local maps constructed from different locations and that it matches the actual layout of the working area well.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.490-500
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• 2000

A new technique for the source location of acoustic emission (AE) in plates whose thichness are close to or thinner than the wavelength has been studied by introducing wavelet transform de-noising technique. The detected AE signals were pre-processed using wavelet transform to be decomposed into the low-frequency, high-amplitude flexural components and the high-frequency, low-amplitude extensional components. If the wavelet transform de-noising was employed, we could successfully filter out the extensional wave component, one of the critical errors of source location in plates by arrival time difference method. The accuracy of source location appeared to be significantly improved and independent of the setting of gain and threshold, plate thickness, sensor-to-sensor distance, and the relative position of source to sensors. Since the method utilizes the flexural component of relatively high amplitude, it could be applied to very large, thin-walled structures in practice.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.352-361
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• 2021

An underwater positioning method that can be applied to structures for underwater construction is being developed at the Korea Institute of Ocean Science and Technology. The method uses an extended Kalman filter (EKF) based on an inertial navigation system for precise and continuous position estimation. The observation matrix was configured to be variable in order to apply asynchronous measured sensor data in the correction step of the EKF. A Doppler velocity logger (DVL) can acquire signals only when attached to the bottom of an underwater structure, and it is difficult to install and recover. Therefore, a complex sensor device for underwater structure attachment was developed without a DVL in consideration of an underwater construction environment, installation location, system operation convenience, etc.. Its performance was verified through a water tank test. The results are the measured underwater position using an ultra-short baseline, the estimated position using only a position vector, and the estimated position using position/velocity vectors. The results were compared and evaluated using the circular error probability (CEP). As a result, the CEP of the USBL alone was 0.02 m, the CEP of the position estimation with only the position vector corrected was 3.76 m, and the CEP of the position estimation with the position and velocity vectors corrected was 0.06 m. Through this research, it was confirmed that stable underwater positioning can be carried out using asynchronous sensors without a DVL.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.64.4-64
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• 2001

Localization is the key role in controlling the Mobile Robot. In this papers, a development of the sensor fusion algorithm for controling UTV(Unmanned Tracked Vehicle) is presented. The multi-sensocial dead-rocking subsystem is established based on the optimal filtering by first fusing heading angle reading from a magnetic compass, a rate-gyro and two encoders mouned on the robot wheels, thereby computing the deat-reckoned location. These data and the position data provoded by LBL system are fused together by means of an extended Kalman filter. This algorithm is proved by simulation studies.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.2
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• pp.148-154
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• 2005

As the exciting point of each phase is determined by the position of rotor, the rotor's accurate position-information is needed for the Switched Reluctance Motor(SRM). When using an absolute-encoder or a resolver, to detect the location of rotor the initial starting is possible, as early sensing of rotor's location is possible. However, this is not appropriate, considering the economical efficiency, and in case of using the incremental-encoder, there's a problem at initial starting as it is not easy to track down the location of rotor at the very beginning. When using Hall-ICs, there's a fault, as it needs a special ring magnet. Considering the initial starting and economical efficiency, the optical sensor technique using a slotted-disk and an opto-interrupter is appropriate, however, this method needs three opto-interrupters and a slotted-disk when using the 6/4 pole SRM. Nevertheless, in this paper, it used only two optical sensors to operate 6/4 pole SRM and made the start up and also forward and reverse operation possible. By excluding the slotted-disc md shortening a optical sensor, it improved the convenience and economical efficiency of the production. Also, as the space for slotted-disc is no more needed, it was able to reduce the size of motor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2073-2078
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• 2016

Recently, there have been many research that recognize the situation using sensors. However, sensor data collection and analysis are still lacking in integration. This is because the data generated by the sensor is difficult to match in terms of metadata and units. Therefore, a methodology for efficiently using data generated from various sensors is needed. In this paper, we propose a system that recognizes the location through information generated from a moving iBeacon. This system constructs the ontology with the data that can recognize the exact position when the patient wearing iBeacon moves in the room. This maps standard items and sensor items, and stores the results of filtering the detected values as knowledge. the system can extract efficient location information by recognizing the value generated by moving the patient carrying iBeacon through the ontology. This can be applied not only to beacons but also to other sensors, and it can be applied variously according to the ontology configuration.