• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.146-156
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• 1998

Thispapr proposes hybrid navigation parameter estimation using sequential aerial images. The proposed navigation parameter estimation system is composed of two parts: relative position estimation and absolute position estimation. the relative position estimation recursively computes the current velocity and absolute position estimation. The relative position estimation recursively computes the current velocity and position of an aircraft by accumulating navigation parameters extracted from two succesive aerial images. Simple accumulation of parameter values decreases reliability of the extracted parameters as an aircraft goes on navigating. therefore absolute position estimation is required to compensate for position error generated in the relative position step. The absolute position estimation algorithm combining image matching and digital elevation model(DEM) matching is presented. Computer simulation with real aerial image sequences shows the efficiency of the proposed hybrial algorithm.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.200-202
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• 2005

In this paper, improved rotor position estimation for position sensorless control system of the SRM (Switched Reluctance Motor) is presented. For more accurate rotor position estimation, the PLL (Phase Locked Loop) based position interpolation is adapted. In the current-flux-rotor position lookup table based rotor position estimation, the inherent current and flux-linkage ripple can cause the position estimation error. Instead of the conventional low-pass filter, the PLL based position interpolation technique is used for the better dynamic performance. The developed rotor position estimation scheme is realized using TMS320F2812 digital signal processor and prototype 1-hp SRM.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.76-84
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• 1999

This paper presents an integrated method for aircraft position estimation using sequential aerial images. The proposed integrated system for position estimation is composed of two parts: relative position estimation and absolute position estimation. Relative position estimation recursively computes the current position of an aircraft by accumulating relative displacement estimates extracted from two successive aerial images. Simple accumulation of parameter values decreases reliability of the extracted parameter estimates as an aircraft goes on navigating, resulting in large position error. Therefore absolute position estimation is required to compensate for the position error generated in relative position estimation. Absolute position estimation algorithms by image matching or digital elevation model (DEM) matching are presented. In image matching, a robust oriented Hausdorff measure (ROHM) is employed whereas in DEM matching an algorithm using multiple image pairs is used. Computer simulation with four real aerial image sequences shows the effectiveness of the proposed integrated position estimation algorithm.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.123-128
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• 2021

This paper present box feature estimation from LiDAR point cluster using maximum likelihood Method. Previous LiDAR tracking method for autonomous driving shows high accuracy about velocity and heading of point cluster. However, Assuming the average position of a point cluster as the vehicle position has a lower accuracy than ground truth. Therefore, the box feature estimation algorithm to improve position accuracy of autonomous driving perception consists of two procedures. Firstly, proposed algorithm calculates vehicle candidate position based on relative position of point cluster. Secondly, to reflect the features of the point cluster in estimation, the likelihood of the particle scattered around the candidate position is used. The proposed estimation method has been implemented in robot operating system (ROS) environment, and investigated via simulation and actual vehicle test. The test result show that proposed cluster position estimation enhances perception and path planning performance in autonomous driving.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1589-1592
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• 1997

Among the prerequisite abilities (perception of environment, path planning and position estimation) of an autonomous mobile robot, position estimation has been seldom studied by mobile robot researchers. In most cases, conventional positioin estimation has been performed by placing landmarks or giving the entrire environmental information in advance. Unlikely to the conventional ones, the study addresses a new method that the robot itself can select distinctive features in the environment and save them as landmarks without any a priori knowledge, which can maximize the autonomous behavior of the robot. First, an orjentaion probaility model is applied to construct a lcoal map of robot's surrounding. The feature of the object in the map is then extracted and the map is saved as landmark. Also, presented is the position estimation method that utilizes the correspondence between landmarks and current local map. In dong this, the uncertainty of the robot's current positioin is estimated in order to select the corresponding landmark stored in the previous steps. The usefulness of all these approaches are illustrated with the results porduced by a real robot equipped with ultrasonic sensors.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.3
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• pp.125-132
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• 2002

PMSMS (permanent magnet synchronous motors) are widely used in industrial applications and home appliances because of their high torque to inertia ratio, superior power density, and high efficiency. For high performance control, accurate informations about the rotor position is essential. Sensorless algorithms have lately been studied extensively due to the high cost of position sensors and their low reliability in harsh environments. A novel position sensorless speed control for PMSMs uses indirect flux estimation and is presented in this paper. Rotor position and angular velocity are estimated by the proposed indirect flux estimation. Linkage flux and magnetic field flux are calculated by the voltage equations and the measured phase current without any integration. Instead of linkage flux calculation with integral operation, indirect flux and differential magnetic field are used for the estimation of rotor position. A proper rejection technique fur current noise effect in the calculation of differential linkage flux is introduced. The proposed indirect flux detecting method is free from the integral rounding error and linkage flux drift problem, because differential linkage flux can be calculated without any integral operation. Furthermore, electrical parameters of the PMSM can be measured by the proposed TCM (time compression method) for soft starting and precise estimation of rotor position. The position estimator uses accurate electrical parameters that are obtained from the proposed TCM at starting strategy. In the operating region, a proper compensation method fur temperature effect can compensate fir the estimation error from the variation of electrical parameters. The proposed novel position sensorless speed control scheme is verified by the experimental results.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.151-156
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• 2014

In this paper, we propose a position estimation method of an entertainment robot in a performance stage. A position information is needed to produce contents of an entertainment robot performance. First, the performance stage is realized by a CD (cadmium sulfide) sensor matrix with a constant distance. Then the proposed position estimation uses ON/OFF information of a CD sensor in a performance stage. We confirmed that the position of the robot is detected with an maximum 4cm in position evaluation experiments. The robot was traveling to the final target position in the walking experiment with 75cm and 120cm path plan. Ultimately, the effectiveness of the proposed estimation is assessed by experimental results of a robot in performance stage. Also, in the proposed system installed by a robot performance contents, there is no necessity to mount a position estimation device on a robot; therefore an advantage of our system is that an entertainment robot commercialized by robot vendor can be utilized in our performance stage directly.

• Journal of Magnetics
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• v.19 no.1
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• pp.90-100
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• 2014

Position estimation that uses only active phase voltage and current is presented, to perform high accuracy position sensorless control of a SRM drive. By extracting the amplitude of the first switching harmonic terms of phase voltage and current for a PWM period through Fast Fourier Transform (FFT), the flux-linkage and position are estimated without external hardware circuitry, such as a modulator and demodulator, which result in increased cost, as well as large position estimation error, produced when the motional back EMF is ignored near zero speed. A two-phase SRM drive system, consisting of an asymmetrical converter and a conventional closed-loop PI current controller, is utilized to validate the performance of the proposed position estimation scheme in comprehensive operating conditions. It is shown that the estimated values very closely track the actual values, in dynamic simulations and experiments.

• Journal of Power Electronics
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• v.9 no.3
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• pp.499-506
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• 2009

In this paper, the initial pole-position estimation of a surface (non-salient) permanent magnet synchronous motor is mathematically analyzed and surveyed on the basis of simulation analysis, and developed for accurate servo motor drive. This algorithm is well carried out under the full closed-loop position control without any pole sensors and is completely insensitive to any motor parameters. This estimation is based on the principle that the initial pole-position is simply calculated by the reverse trigonometric function using the two feedback currents in the full closed-loop position control. The proposed algorithm consists of the predefined reference position profile, the information of feedback currents, speed, and relative position, and the reverse trigonometric function for the initial-pole position estimation. Comparing with the existing researches, the mathematical analysis is introduced to get a more accurate initial pole-position of the surface permanent magnet motor under the closed-loop position control. It is found that the proposed algorithm can be easily applied in servo drive applications because it satisfies the following user's specifications; accuracy and moving distance.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.330-336
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• 1996

An real-time active beacon localization system for mobile robots is developed and implemented. This system permits the estimation of robot positions when detecting light sources by PSD(Position Sensitive Detector) sensor which are placed sparsely over the robots work space as beacons(or landmarks). An LSE(Least Square Estimation) method is introduced to calibrate the internal parameters of a model for the beacon and robot position. The proposed system has two operational modes of position estimation. One is the initial position calculation by the detection of two or more light sources positions of which are known. The other is the continuous position compensation that calculates the position and heading of the robot using the IEKF(Iterated Extended Kalman Filter) applied to the beacon and dead-reckoning data. Practical experiments show that the estimated position obtained by this system is precise enough to be useful for the navigation of robots.