• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.544-547
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• 1997

In this paper, we propose a dynamic localization method using a rotating sonar and a map. The proposed method is implemented by using extended Kalman filter. The state equation is based on the encoder propagation model and the encoder error model, and the measurement equation is a map-based measurement equation using a rotating sonar sensor. By utilizing sonar beam characteristics, map-based measurements are updated while AMR is moving continuously. By modeling and estimating systematic errors of a differential encoder, the position is successfully estimated even the interval of the map-based measurement. Monte-Carlo simulation shows that the proposed global position estimator has the performance of a few millimeter order in position error and of a few tenth degrees in heading error and of compensating systematic errors of the differential encoder well.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.12
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• pp.1216-1222
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• 2010

Based on the MacDonald's analytic model for the diffracted sound field of a semi-infinite noise barrier, computer simulations were performed for various positions of error microphones for an active noise barrier system. The simulation process also included the effects of floor reflections on both sides of the barrier. The results were also compared with Niu's simulation results and showed a straight line arrangement of sensors and actuators, in the order of primary source, secondary source and error microphone is better than over the top arrangement of the error microphones.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.3
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• pp.293-301
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• 2019

Based on accurate image processing technology, a system for measuring displacement in ${\mu}m$ for drive error (position error, straightness error, flatness error) at a distance using parallel light and image sensor is developed, and a system for applying this technology development to a large 3D rapid prototyping machine and compensating in real time is developed to dramatically reduce the range of measurement error and enable intelligent 3D production of high quality products.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1436-1449
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• 2009

The value of sensing information is decided according to positions of sensor nodes, which are very important in sensor networks. In this paper, we propose a method that estimates positions of nodes by using adjacent node information and received signal strength in a sensor network. With the proposed method, we can find positions of nodes easily because we use information that nodes have. Moreover, we can find distribution easily for all the nodes because we can measure a relative position for a node whose position is not known based on anchor nodes whose positions are already known. We utilized Use case diagram, activity diagram and State machine diagram among several diagrams of UML to implement proposed method in sensor networks that is dynamic system. We can understand exact flow for each function of the proposed method in node position estimation system can be implemented easily. And we can be confirmed that the position of estimated nodes has a little error.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.123-129
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• 2009

It is important to locate nodes in the research of wireless sensor network. In this paper, we propose a method that estimates the positions of nodes by using adjacent node information and signal strength in wireless sensor network. With this method, we can find positions of nodes easily because we use Information that nodes have. And we can make a map for all the nodes because we can measure a relative position for an node whose position is not known based on anchor nodes whose positions are already known. In addition, we can confirm whether nodes are placed appropriately. We confirmed that we can locate positions of unknown nodes with small error through verifying the proposed method.

• Journal of Ocean Engineering and Technology
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• v.19 no.6 s.67
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• pp.78-85
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• 2005

Initial alignment and localization are important topics in inertial navigation systems, since misalignment and initial position error wholly propagate into the navigation systems and deteriorate the performance of the systems. This paper presents the error convergence characteristics of the hybrid navigation system for underwater vehicles initial position, which is based on an inertial measurement unit (IMU) accompanying a range sensor. This paper demonstrates the improvement on the navigational performance oj the hybrid system with the range information, especially focused on the convergence of the estimation of underwater vehicles initial position error. Simulations are performed with experimental data obtained from a rotating ann test with a fish model. The convergence speed and condition of the initial error removal for random initial position errors are examined with Monte Carlo simulation. In addition, numerical simulation is conducted with an AUV model in lawn-mowing survey mode to illustrate the error convergence of the hybrid navigation System for initial position error.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.159-166
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• 2012

There are several ways such as GPS(Global Positioning System) and INS (Inertial Navigation System) to track the location of moving vehicle. The GPS has the advantages of having non-accumulative error even if it brings about errors. In order to obtain the position information, we need to receive at least 3 satellites information. But, the weak point is that GPS is not useful when the 혠 signal is weak or it is in the incommunicable region such as tunnel. In the case of INS, the information of the position and posture of mobile with several Hz~several hundreds Hz data speed is recorded for velocity, direction. INS shows a very precise navigational performance for a short period, but it has the disadvantage of increasing velocity components because of the accumulated error during integration over time. In this paper, sensor fusion algorithm is applied to both of INS and GPS for the position information to overcome the drawbacks. The proposed system gets an accurate position information from experiment using SVD in a non-accessible GPS terrain.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.268-274
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• 2013

In this paper, the performance analysis of optics-based sensor node localization using ToF (Time of Flight) scheme is conducted. Generally, the position of the sensor node is calculated on the base station. And the base station scans neighboring sensor nodes with a laser. The laser which is reflected from one sensor node, however, can be reached to the base station at different angles according to the scanning resolution. This means that the error of the reached angle can increase and one node may be recognized as different nodes. Also the power of laser can decrease because the laser signal spread. Thus the sensor node which is located at a long distance from the base station cannot be detected. In order to overcome these problems which can be occurred in localization using ToF, the beam spot, the scanning resolution, the size of reflector and the power of laser at the sensor node were analyzed. It can be expected that the consequence of analysis can be provided in acquisition of accurate position of sensor node and construction of optics-based sensor node localization system.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.96-103
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• 2014

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.566-573
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• 2014

This paper presents the results of an integrated navigation performance analysis for selecting the sensor of an unmanned underwater vehicle (UUV) using Monte Carlo numerical simulation. An inertial measurement unit (IMU) and Doppler velocity log (DVL) are considered to build the integrated navigation system. The position error and price of the sensor are selected as performance indices to evaluate the volunteer integrated navigation systems. Monte-Carlo simulation is introduced to analyze the circular error probability (CEP) and its variance. Simulation results provide the proper sensor combination for integrated navigation in relation to the performance and price.