• International Journal of Aeronautical and Space Sciences
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• v.11 no.1
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• pp.31-40
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• 2010

For weapon cueing and Head-Mounted Display (HMD), it is essential to continuously estimate the motion of the helmet. The problem of estimating and predicting the position and orientation of the helmet is approached by fusing measurements from inertial sensors and stereo vision system. The sensor fusion approach in this paper is based on nonlinear filtering, especially expended Kalman filter(EKF). To reduce the computation time and improve the performance in vision processing, we separate the structure estimation and motion estimation. The structure estimation tracks the features which are the part of helmet model structure in the scene and the motion estimation filter estimates the position and orientation of the helmet. This algorithm is tested with using synthetic and real data. And the results show that the result of sensor fusion is successful.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.11
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• pp.763-770
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• 2000

The speed and position information of the rotor are required in the speed control of SRM(Switched Reluctance Motors). This information is generally provided by shaft encoder or resolver. It is weak in the dusty, high temperature, and EMI environment. Consequntly, much attention has been given to SRM control for eliminationating the position and speed sensors. In this paper, a new estimation algorithm for the rotor position and speed for SRM drives is described. The algorithm is implemented by the sliding mode observer. The stability and robustness of the sliding observer for the parameter variations of the SRM are proved by variable structure control theory. Speed control of the SRM is accomplished by the estimated speed and position. Experiment results verify that the mode observer is able to estimate the speed and position well.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.111-116
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• 2008

Radar system must estimate exactly quickness and target in interference channel. Because interference of radio channel is multipath channel by artificial structure and nature structure. signal estimation is difficult. As long as, get rid of interference signal have been study digital beamforming, adaptive array antenna and so on. In this paper, proposed SPT-SALCMV beamforming algorithm get rid of coherent interference algorithm and adaptive array antenna. Adaptive array forms null pattern and reduces gains for direction of interference signal. And estimate signal that want by keeping gains of beam pattern changelessly to target signal direction. In this paper, proposed SPT-SALCMV algorithm was exactly received position of target. But general SPT-LCMV algorithm resulted beam error about 30degrees. Therefore, proved that SPT-SALCMV algerian that propose in this paper is more excellent than genaral SPT-LCMV algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.119-126
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• 2002

In this paper, we present a new approach based on an elitist genetic algorithm for the task of aligning the position of a robot gripper using CCD cameras. The vision-based control scheme for the task of aligning the gripper with the desired position is implemented by image information. The relationship between the camera space location and the robot joint coordinates is estimated using a camera-space parameter modal that generalizes known manipulator kinematics to accommodate unknown relative camera position and orientation. To find the joint angles of a robot manipulator for reaching the target position in the image space, we apply an elitist genetic algorithm instead of a nonlinear least square error method. Since GA employs parallel search, it has good performance in solving optimization problems. In order to improve convergence speed, the real coding method and geometry constraint conditions are used. Experiments are carried out to exhibit the effectiveness of vision-based control using an elitist genetic algorithm with a real coding method.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.11
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• pp.664-670
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• 2004

This paper presents a new velocity estimation strategy of a non-salient permanent magnet synchronous motor (PMSM) drive without high frequency signal injection or special PWM pattern. This approach is based on the d-axis current regulator output voltage of the drive system that has the information of rotor position error. The rotor velocity can be estimated through a rotor position tracking PI controller that controls the position error to zero. For zero and low speed operation, PI controller gains of rotor position tracking controller have a variable structure according to the estimated rotor velocity. In order to boost the bandwidth of PI controller around zero speed, a loop recovery technique is applied to the control system. The proposed method only requires the flux linkage of permanent magnet and is insensitive to the parameter estimation error and variation. The designers can easily determine the possible operating range with a desired bandwidth and perform the vector control even at low speeds. The experimental results show the satisfactory operation of the proposed sensorless algorithm under rated load conditions.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.91-94
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• 2001

In this paper, we proposed localization method of mobile robot using color landmark mounted on ceiling. This work is composed 2 parts : landmark recognition part which finds the position of multiple landmarks in image and identifies them and absolute position estimation part which estimates the location and orientation of mobile robot in indoor environment. In landmark recognition part, mobile robot detects artificial color landmarks using simple histogram intersection method in rg color space which is insensitive to the change of illumination. Then absolute position estimation part calculates relative position of the mobile robot to the detected landmarks. For the verification of proposed algorithm, ceiling-orientated camera was installed on a mobile robot and performance of localization was examined by designed artificial color landmarks. As the result of test, mobile robot could achieve the reliable landmark detection and accurately estimate the position of mobile robot in indoor environment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.756-761
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• 2013

This paper propose the new demodulation method that can detect resolver signal's peak at the time of position estimation when the position information is required during current controller period. The proposed method is performed in a synchronous demodulation way with exciting signal and also cover a capability which can compensate the lag element of exciting signal caused by the resolver's inductive component and filter circuit. This paper carried out the experiment to investigate the validity and performance of the suggested method by using the test board made up of DSP and demodulation circuit. The test results show that the proposed method is theoretically clear and work completely as expected from making sure of sampling resolver signal's peak at the time of position estimation. In addition, Software position tracking algorithm is executed with the demodulated signals generated by the suggested method and an exact position can be estimated.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.40-47
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• 2007

Recently, with the development of service robots and with the new concept of ubiquitous world, the position estimation of mobile objects has been raised to an important problem. As pre-liminary research results, some of the localization schemes are introduced, which provide the absolute location of the moving objects subjected to large errors. To implement a precise and convenient localization system, a new absolute position estimation method for a mobile robot in indoor environment is proposed in this paper. Design and implementation of the localization system comes from the usage of active beacon systems (based upon RFID technology). The active beacon system is composed of an RFID receiver and an ultra-sonic transmitter: 1. The RFID receiver gets the synchronization signal from the mobile robot and 2. The ultra-sonic transmitter sends out the traveling signal to be used for measuring the distance. Position of a mobile robot in a three dimensional space can be calculated basically from the distance information from three beacons and the absolute position information of the beacons themselves. Since it is not easy to install the beacons at a specific position precisely, there exists a large localization error and the installation time takes long. To overcome these problems, and provide a precise and convenient localization system, a new auto calibration algorithm is developed in this paper. Also the extended Kalman filter has been adopted for improving the localization accuracy during the mobile robot navigation. The localization accuracy improvement through the proposed auto calibration algorithm and the extended Kalman filter has been demonstrated by the real experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.7-12
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• 2012

In this paper, we present an effective viewpoint estimation algorithm for the Moving parallax barrier method of 3D display mobile device. Moving parallax barrier is designed to overcome the biggest problem, the limited view angle. To accomplish it, the position of the viewer's eyes or face should be estimated with strong stability and no latency. We focus on these requirements in the poor performance of mobile processors. We used a pre-processing algorithm in order to overcome the various illumination changes. And, we combined the conventional Viola-Jones face detection method and Optical-flow algorithm for robust and stable viewpoint estimation. Various computer simulations prove the effectiveness of the proposed method.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.517-523
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• 2011

The estimation filter in radar systems must track targets' position within low tracking error. In the Multi-Function Radar(MFR), ${\alpha}-{\beta}$ filter and Kalman filter are widely used to track single or multiple targets. However, due to target maneuvering, these filters may not reduce tracking error, therefore, may lost target tracks. In this paper, a target tracking filter based on particle filtering algorithm is proposed for the MFR. The advantage of this method is that it can track targets within low tracking error while targets maneuver and reduce impoverishment of particles by the proposed resampling method. From the simulation results, the improved tracking performance is obtained by the proposed filtering algorithm.