• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.423-423
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• 2000

This paper proposes an effective algorithm for following a wall by an autonomous mobile robot with sonar sensors and infrared sensors in an indoor environment. The proposed method uses deadreckoning to estimate the current position and orientation of a mobile robot. Sonar sensor data are used to estimate shape and position of wall using proposed algorithm. Infrared sensor data are used as assistant when sonar sensor data is uncertain. Simulation results using mobile robot show that the proposed algorithm is proper for the following wall.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.3
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• pp.471-479
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• 2019

This research proposes a indoor magnetic map matching algorithm that improves the position accuracy by employing multiple magnetic sensors and probabilistic candidate weighting function. Since the magnetic field is easily distorted by the surrounding environment, the distorted magnetic field can be used for position mapping, and multiple sensor configuration is useful to improve mapping accuracy. Nevertheless, the position error is likely to increase because the external magnetic disturbances have repeated pattern in indoor environment and several points have similar magnetic field distortion characteristics. Those errors cause large position error, which reduces the accuracy of the position detection. In order to solve this problem, we propose a method to reduce the error using multiple sensors and likelihood boundaries that uses human walking characteristics. Also, to reduce the maximum position error, we propose an algorithm that weights according to their importance. We performed indoor walking tests to evaluate the performance of the algorithm and analyzed the position detection error rate and maximum distance error. From the results we can confirm that the accuracy of position detection is greatly improved.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1512-1515
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• 1997

One of the advantages of master-slave teleoperation is scaling concept such as position scaling, force scaling Meanuhile, lots of quantization effects are generated from position and force sensors in the master and slave manipulator. In this paper, to show the output error caused by the quantizaion effects from the position sensor and position scaling factor, simulation is done for free motion without contact in slave side. Transfer functiion model in which the quantization effect is assumed to be a disturbance input to the system is derived. Model shows that Jacobian, scaling factors, and controller affect the output by quantization effects form esnsors. One dof master and slave are used for simulation. In our study, the higher sensor resolution decreases the output error form quantization. Scaling factors can amplify the quantizatiion effects form the sensors in master and slave manipulators.

• Journal of Sensor Science and Technology
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• v.14 no.4
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• pp.225-230
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• 2005

This paper describes a novel tip position sensor made of a triangularly shaped piezoelectric PVDF (polyvinylidene fluoride) film for a cantilever beam. Due to the boundary condition of the cantilever beam and the spatial sensitivity function of the sensor, the charge output of the sensor is proportional to the tip position of the beam. Experimental results with the PVDF sensor were compared with those using two commercially available position sensors: an inductive sensor and an accelerometer. The resonance frequencies of the test beam, measured using the PVDF sensor, matched well with those measured with the two commercial sensors and the PVDF sensor also showed good coherence over wide frequency range, whereas the inductive sensor became poor above a certain frequency.

• Journal of Sensor Science and Technology
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• v.22 no.2
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• pp.111-117
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• 2013

The autonomous driving method using magnetic sensors recognizes the position by measuring magnetic fields in autonomous robots or vehicles after installing magnetic markers in a moving path. The Position estimate method using magnetic sensors has an advantage of being affected less by variation of driving environment such as oil, water and dust due to the use of magnetic field. It also has the advantages that we can use the magnet as an indicator and there is no consideration for power and communication environment. In this paper, we propose an efficient sensor system for an autonomous driving vehicle supplemented for existing disadvantage. In order to efficiently eliminate geomagnetism, we analyze the components of the horizontal and vertical magnetic field. We propose an algorithm for position estimation and geomagnetic elimination to ease analysis, and also propose an initialization method for sensor applied in the vehicle. We measured and analyzed the developed system in various environments, and we verify the advantages of proposed methods.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.209-218
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• 2019

This study proposes a new approach to Control the Orientation and position based on obstacle avoidance technology by multi sensors fusion and autonomous travelling control of mobile robot system for implimentation of Smart FA. The important focus is to control mobile robot based on by the multiple sensor module for autonomous travelling and obstacle avoidance of proposed mobile robot system, and the multiple sensor module is consit with sonar sensors, psd sensors, color recognition sensors, and position recognition sensors. Especially, it is proposed two points for the real time implementation of autonomous travelling control of mobile robot in limited manufacturing environments. One is on the development of the travelling trajectory control algorithm which obtain accurate and fast in considering any constraints. such as uncertain nonlinear dynamic effects. The other is on the real time implementation of obstacle avoidance and autonomous travelling control of mobile robot based on multiple sensors. The reliability of this study has been illustrated by the computer simulation and experiments for autonomous travelling control and obstacle avoidance.

• Journal of the Ergonomics Society of Korea
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• v.36 no.5
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• pp.395-409
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• 2017

Objective: The purpose of this study was to optimize the number and positions of foot pressure sensors using the reliability analysis of the center of pressure (COP) in smart shoes. Background: Foot pressure can be different according to foot region, and it is important which region of the foot pressure needs to be measured. Method: Thirty adults (age: $20.5{\pm}1.8years$, body weight: $71.4{\pm}6.5kg$, height: $1.76{\pm}0.04m$) participated in this study. The foot pressure data were collected using the insole of Pedar-X system (Novel GmbH, USA) with a sampling frequency of 100Hz during 1.3m/s speed walking on the treadmill (Instrumented treadmill, Bertec, USA). The intraclass correlation coefficients (ICC) were calculated between the COP positions using 4, 5, 6, 7, 8, and 99 sensors, while one-way repeated measure ANOVA was performed between the standard deviation (SD) of the COP positions. Results: The medio-lateral (M/L) COP position using 99 sensors was positively correlated with the M/L COP positions using 6, 7, and 8 sensors; however, it was not correlated with the M/L COP positions using 4 and 5 sensors during landing phase (1~4%) (p<.05). The antero-posterior (A/P) COP position using 99 sensors was positively correlated with the A/P COP positions using 4, 5, 6, 7, and 8 sensors (p<.05). The SD of the COP position using 99 sensors was smaller than the SD of the M/L COP positions using 4, 5, 6, 7, and 8 sensors (p<.05). Conclusion: Based on our findings, it is desirable to arrange at least 6 sensors in smart shoes. Application: The study of optimizing the number and positions of foot pressure sensors would contribute to developing more effective smart shoes using foot pressure technology.

• Journal of Magnetics
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• v.21 no.2
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• pp.173-178
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• 2016

Six-step commutation control widely used in brushless DC (BLDC) motor can be applied to consequent pole permanent magnet (CPPM) belt starter generator (BSG) with trapezoidal back electromotive force (EMF) in the starter state. However, rotor position detection with three Hall sensors in BLDC motor can hardly be employed in CPPM BSG due to asymmetric flux distribution in each pole side of CPPM BSG. This paper presents a low-cost rotor position detection method for CPPM BSG in which six Hall sensors are proposed to be used based on the analysis of flux distribution by 3D FEA. In the method, the six Hall sensors are divided into three groups and two signals in each group are combined through performing logic operations. In addition, offset angle between back EMF and the related Hall signal can be compensated by moving the Hall sensors. Experiments of a 2 kW CPPM BSG prototype have also been performed to verify the proposed method.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.3
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• pp.246-251
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• 2012

This paper proposes a new position compensation method for misaligned Hall-effect sensors of BLDCM(Brushless DC Motor). If the Hall-effect sensors are installed at wrong position, the exact rotor position cannot be obtained. Therefore, when the BLDCM is controlled with this wrong position, the torque ripple can be increased and the average torque also decreases. The back-EMF of BLDCM can be obtained by using the voltage equation and by multiplying the back-EMF constant and rotor speed. At a constant speed, the estimated back-EMF by using the multiplication of the back-EMF constant and rotor speed is constant, but the estimated back-EMF from the voltage equation decreases at the commutation point because the line-to-line back-EMF of two conducting phases is start to decrease at this point. Therefore, by using the difference between these two estimated back-EMFs, the commutation point of the phase current can be determined and position compensation can be carried out. The proposed position correction method doesn't require additional hardware circuit and can be easily implemented. The validity of the proposed position compensation method is verified through several experiments.

• Journal of Sensor Science and Technology
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• v.32 no.4
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• pp.232-237
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• 2023

This paper presents a system for estimating the position of a magnet using a magnetic sensor. An algorithm is presented to analyze the waveform and output voltage values of the magnetic field generated at each position when the magnet moves and to estimate the position of the magnet based on the analyzed data. Here, the magnet is sufficiently small to be inserted into a blood vessel and has a micro-magnetic field of hundreds of nanoteslas owing to the small size and shape of the guide wire. In this study, a highly sensitive magneto-impedance (MI) sensor was used to detect these micro-magnetic fields. Nine MI sensors were arranged in a 3×3 configuration to detect a magnetic field that changes according to the position of the magnet through the MI sensor, and the voltage value output was polynomially regressed to specify a position value for each voltage value. The accuracy was confirmed by comparing the actual position value with the estimated position value by expanding it from a 1D straight line to a 3D space. Additionally, we could estimate the position of the magnet within a 3% error.