• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.960-973
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• 2018

This paper presents design for error correcting algorithm of the time of flight (ToF) detection value in the light detection and ranging (LIDAR) system sensor. The walk error of ToF value is generated by change of the received signal power depending on distance between the LIDAR sensor and object. The proposed method efficiently compensates the ToF value error by the independent ToF value calculation from the received signal using both rising point and falling point. A constant error of ~0.05 m is obtained after the walk error correction while an increasing error up to ~1 m is obtained with conventional method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.11
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• pp.2688-2695
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• 2000

In multi-axis force sensor, compliance matrices representing structural behaviour of internal sensor bodies play an important role in decoupled sensing and accuracy, Recently, error propagation through compliance matrices has been studied via approximation approach. However the upper bound of measured force error has not been known. In this paper, error propagation in force sensing is analysed in a unified way when both strain measurement error and compliance matrix error exist, and the upper bound of the measured force error is derived exactly(not approximately). The analysis is examined through a numerical example.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.2
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• pp.65-67
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• 2006

To make the autonomous mobile robot move in the unknown space, we have to know the information of current location of the robot. So far, the location information that was obtained using Encoder always includes Dead Reckoning Error, which is accumulated continuously and gets bigger as the distance of movement increases. In this paper, we analyse the effect of the size of the two wheels of the mobile robot and the wheel track of them among the factors of Dead Reckoning Error. And after this, we compensate this Dead Reckoning Error by Kalman filter using Gyro Sensors. To accomplish this, we develop the controller to analyse the error components of Gyro Sensor and to minimize the error values. We employ the numerical approach to analyse the error components by linearizing them because each error component is nonlinear. And we compare the improved result through simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4B
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• pp.208-216
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• 2007

Wireless Sensor Networks (WSNs) are characterized by low capacity on each nodes and links. Wireless links have high bit error rate (BER) parameter that changes frequently due to the changes on network topology, interference, etc. To guarantee reliability in an error-prone environment, a retransmission mechanism can be used. In this mechanism, the number of retransmissions is used as a parameter that controls reliability requirement level. In this paper, we propose an Error Adaptive Transport Protocol (EATP) for WSNs that updates the number of retransmissions regularly to guarantee reliability during bit error rate changes as well as to utilize energy effectively. The said algorithm uses local information, thus, it does not create overhead problem.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.323-334
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• 2014

In this paper, we proposed indoor positioning system with improved accuracy. The proposed indoor location measurement system is based pedestrian location measurement method that use the embedded sensor of smartphone. So, we do not need wireless external resources, such as GPS or WiFi signals. The conventional methods measure indoor location by generating a movement route of pedestrian by step and direction recognition. In this paper, to correct the direction sensor error, we use the common feature of the normal indoor floor map that the indoor path is lattice-structured. And we quantize moving directions depending on the direction of indoor path. In addition, we propose moving direction measuring method using geomagnetic sensor and gyro sensor to improve the accuracy. Also, the proposed step detection method uses angle and accelerometer sensors. The proposed step detection method is not affected by the posture of the smartphone. Direction errors caused by direction sensor error is corrected due to proposed moving direction measuring method. The proposed location error correction method corrects location error caused by step detection error without the need for external wireless signal resources.

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.205-215
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• 2012

A GPS sensor is widely used in many areas such as navigation, or air traffic control. Particularly, the car navigation system is equipped with GPS sensor for locational information. However, when a car goes through a tunnel, forest, or built-up area, GPS receiver cannot get the enough number of satellite signals. In these situations, a GPS receiver does not reliably work. A GPS error can be formulated by sum of bias error and sensor noise. The bias error is generated by the geometric arrangement of satellites and sensor noise error is generated by the corrupted signal noise of receiver. To enhance GPS sensor accuracy, these two kinds of errors have to be removed. In this research, we make the road database which includes Road Database File (RDF). RDF includes road information such as road connection, road condition, coordinates of roads, lanes, and stop lines. Among the information, we use the stop line coordinates as a feature point to correct the GPS bias error. If the relative distance and angle of a stop line from a car are detected and the detected stop line can be associated with one of the stop lines in the database, we can measure the bias error and correct the car's location. To remove the other GPS error, sensor noise, the Kalman filter algorithm is used. Additionally, using the RDF, we can get the information of the road where the car belongs. It can be used to help the GPS correction algorithm or to give useful information to users.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.342-344
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• 2006

During last years, large investments have been directed to development and research of nano-technological products like semiconductor, display panel, optic-fiber communication components, life technology, and ultra-precision components. All quantitative measurements at nanometre scale should guarantees accurate results and high quality. Laser interferometer is one of most famous nanometre scale devices to be able to measure metre-scale distance with nanometre scale resolution, but it is easily affected by various error causes like geometrical, instrumental and environmental factor. On the other side, capacitive sensor is robust to above error factors, but it is able to measure relatively shorter distance, under $100{\mu}m$, than laser interferometer. New error correction method for laser interferometry using capacitive sensor will be introduced in this paper.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1201-1211
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• 2015

WSN acts as an effective tool for tracking the large scale environments. In such environment, the battery life of the sensor networks is limited due to collection of the data, usage of sensing, computation and communication. To resolve this, a mobile robot is presented to identify the data present in the partitioned sensor networks and passed onto the sink. In novel data collection algorithm, the performance of the data collecting operation is reduced because mobile robot can be used only within the limited range. To enhance the data collection in a changing environment, Non Linear Error Identifier (NLEI) algorithm has been developed and presented in this paper to configure the robot by means of error models which are non-linear. Experimental evaluation has been conducted to estimate the performance of the proposed NLEI and it has been observed that the proposed NLEI algorithm increases the error correction rate upto 42% and efficiency upto 60%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04a
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• pp.637-642
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• 1995

For measuring the error motion of ultra-precision spindle, eliminating the geometric errors is a must. Unless it is achieved, geometric errors will be dominant in data. Here, the roundness error and alignment error between spindle and sensor are to be removed. That's because typical error range of such spindle is muchless than geometric one. A capacitive transducer of cylidricalshape was developed, which takes full advantage of the spatial-averaging effect by using large area compared tpo the geometric error. This idea was first proposed by Chapman and here it is modified for better performance with nomical gap of 50 .mu. m and with newly designed guards which encompass the respective sensor to rectify the electrical field distribution in good shape. The measurement system is made to get the orbit of Ultra-Precision Air Spindle which is supposed to have its runout under 1 .mu. m. The Calibration data of this sensor is presented and the spindle orbit from 2000rpm to 5500rpm is showed. It is quite reasonable to use this sensor in the range of 60 .mu. m with an accuracy of several tens of nm.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1040-1047
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• 2011

This paper proposes a novel method based on error back propagation neural networks to fuse laser sensor data and ultrasonic sensor data for enhancing the accuracy of mapping. For navigation of single robot, the robot has to know its initial position and accurate environment information around it. However, due to the inherent properties of sensors, each sensor has its own advantages and drawbacks. In our system, the robot equipped with seven ultrasonic sensors and a laser sensor navigates to map two different corridor environments. The experimental results show the effectiveness of the heterogeneous sensor fusion using an error backpropagation algorithm for mapping.