• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.856-859
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• 1996

In this paper, a coarse alignment algorithm for strapdown inertial navigation system is proposed and evaluated analytically. The algorithm computes roll and pitch angles of the vehicle using accelerometer outputs, and then determines yaw angle with gyro outputs. It is referred, as two-step coarse alignment in this work. With the geometric relation between sensor outputs and roll, pitch and yaw angles, the algorithm error is analytically derived and compared with the previous coarse alignment algorithm introduced by Britting. The results show that the proposed two-step coarse alignment algorithm has better performance for pitch angle computation.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.674-679
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• 1998

In this paper, a new coarse alignment algorithm is proposed for roughly determining the initial attitude of the vehicle. The algorithm, referred as two-step coarse alignment algorithm, computes roll and pitch angle of the vehicle using accelerometer outputs, and then determines yaw angle with gyro outputs. With the geometric relation between sensor outputs and attitude angles, the algorithm error is analytically derived and compared with the previous coarse alignment algorithm that computes a transformation matrix using accelerometer md gyro outputs simultaneously. The simulation is also performed by varying the sensor errors. The results show that the proposed two-step coarse alignment algorithm has better performance for east tilt angle.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1233-1240
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• 2010

In the flat panel display and semiconductor industries, the visual alignment system is considered as a core technology which determines the productivity of a manufacturing line. It consists of the vision system to extract the centroids of alignment marks and the stage control system to compensate the alignment error. In this paper, we develop a Kalman filter algorithm to estimate the alignment mark postures and propose a coarse-fine alignment control method which utilizes both original fine images and reduced coarse ones in the visual feedback. The error compensation trajectory for the distributed joint servos of the alignment stage is generated in terms of the inverse kinematic solution for the misalignment in task space. In constructing the estimation algorithm, the equation of motion for the alignment marks is given by using the forward kinematics of alignment stage. Secondly, the measurements for the alignment mark centroids are obtained from the reduced images by applying the geometric template matching. As a result, the proposed Kalman filter based coarse-fine alignment control method enables a considerable reduction of alignment time.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.3
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• pp.565-573
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• 2017

This paper presents a multistage in-flight alignment (MIFA) method for a strapdown inertial navigation system (SDINS) suitable for moving vehicles with no initial attitude references. A SDINS mounted on a moving vehicle frequently loses attitude information for many reasons, and it makes solving navigation equations impossible because the true motion is coupled with an undefined vehicle attitude. To determine the attitude in such a situation, MIFA consists of three stages: a coarse horizontal attitude, coarse heading, and fine attitude with adaptive Kalman navigation filter (AKNF) in order. In the coarse horizontal alignment, the pitch and roll are coarsely estimated from the second order damping loop with an input of acceleration differences between the SDINS and GPS. To enhance estimation accuracy, the acceleration is smoothed by a scalar filter to reflect the true dynamics of a vehicle, and the effects of the scalar filter gains are analyzed. Then the coarse heading is determined from the GPS tracking angle and yaw increment of the SDINS. The attitude from these two stages is fed back to the initial values of the AKNF. To reduce the estimated bias errors of inertial sensors, special emphasis is given to the timing synchronization effects for the measurement of AKNF. With various real flight tests using an UH60 helicopter, it is proved that MIFA provides a dramatic position error improvement compared to the conventional gyro compass alignment.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.2
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• pp.138-145
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• 2000

In this paper an initial alignment algorithm for a strapdown inertial navigation system is implemented using a RISC CPU board. The algorithm computes roll pitch and yaw angles of the direction cosine matrix utilizing measured components of the specific force and earth rate when the navigation system is stationary. The coarse alignment algorithm is performed first and then the fine alignment algorithm containing a 3rd-order gyrocompass loop follows. The experimental set consists of an IMU a CPU board and a monitoring system Experimental results show that the implemented algorithm can be utilized in navigation systems.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.355-359
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• 2006

For the poor observability of azimuth misalignment angle and east gyro drift rate of the traditional initial alignment, a bran-new SINS stationary fast self-alignment approach is proposed. By means of analyzing the characteristic of the strapdown inertial navigation system (SINS) stationary alignment seriously, the new approach takes full advantage of the specific force and angular velocity information given by inertial measurement unit (IMU) instead of the mechanization of SINS. Firstly, coarse alignment algorithm is presented. Secondly, a new fine alignment model for SINS stationary self-alignment is derived, and the observability of the model is analysed. Then, a modified Sage-Husa adaptive Kalman filter is introduced to estimate the misalignment angles. Finally, some computer simulation results illustrate the efficiency of the new approach and its advantages, such as higher alignment accuracy, shorter alignment time, more self-contained and less calculation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.273-277
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• 2003

A general process of electronic assembly is composed of a series of geometric alignments and bonding/screwing processes. After assembly, the function is tested in a following process of inspection. However, assembly of micro-optic devices requires both processes to be performed in equipment. Coarse geometric alignment is made by using vision and optical function is improved by the following fine motion based on feedback of tunable laser interferometer. The general system is composed of a precision robot system for 3D assembly, a 3D vision guided system for geometric alignment and an optical feedback system with a tunable laser. In this study, we propose a new fast alignment algorithm of micro-optic devices for both of visual and optical alignments. The main goal is to find a fastest alignment process and algorithms with state-of-the-art technology. We propose a new approach with an optimal sequence of processes, a visual alignment algorithm and a search algorithm for an optimal optical alignment. A system is designed to show the effectiveness and efficiency of the proposed method.

• Journal of Computational Design and Engineering
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• v.1 no.4
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• pp.223-232
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• 2014

This paper describes a variant of the extended Gaussian image based registration algorithm for point clouds with surface color information. The method correlates the distributions of surface normals for rotational alignment and grid occupancy for translational alignment with hue filters applied during the construction of surface normal histograms and occupancy grids. In this method, the size of the point cloud is reduced with a hue-based down sampling that is independent of the point sample density or local geometry. Experimental results show that use of the hue filters increases the registration speed and improves the registration accuracy. Coarse rigid transformations determined in this step enable fine alignment with dense, unfiltered point clouds or using Iterative Common Point (ICP) alignment techniques.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1688-1692
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• 2003

The automatic Landing system is used for the automatic functions of automatic transfer crane in the automated container terminal. It confirms and adjusts the alignment and pose between spreader and container and accomplishes the automatic loading/unloading job of containers in yard. Specially, it is required in the automated container terminal and is well adapted under the coarse external environments. This system used the laser sensors to recognize the alignment between spreader and container. In this paper the algorithm of recognition of the alignment and pose is presented and the result of its simulation is shown.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.112-123
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• 1994

In this paper, inspection and subpixed alignment algorithms of SMD's (Surface Mounting Devices) using fuzzy morphology are proposed. First, camera calibration is performed and then the inspection algorithm detects defects such as lead bending and breaking using the ruler generated by fuzy morphology. The SMD having no defects is tested whether it is mounted in the specified position or not. The proposed subpixel alignment algorithm detects accurately orientation and position using subpixel interpolation. It consists of two parts: preprocessing and main processing steps, in which corner points and coarse orientation of a SMD are detected, and interpolation is used to obtain final parameters with wubpixel accuracy. The computer simulation shows that the proposed algorithms give more accurate parameters, and they can be applied to fast and accurate automatic surface mounting systems.