• Journal of Korea Game Society
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• v.20 no.6
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• pp.43-52
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• 2020

This paper presents a fast pattern tracking method using location prediction in cubemap video for 360-degree VR. A spherical cubemap frame has six face textures and searching a pattern is much slower than a flat image. To overcome the limitation, we propose a method of predicting the location of target pattern using Kalman filter and reducing the search area by considering only textures of predicted location. The experimental results showed that the proposed system is much faster than the previous method of searching all six faces and also gives accurate pattern tracking performance.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.103-106
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• 2003

In this paper, we present a hybrid inertial and vision-based tracking system for VR applications. One of the most important aspects of VR (Virtual Reality) is providing a correspondence between the physical and virtual world. As a result, accurate and real-time tracking of an object's position and orientation is a prerequisite for many applications in the Virtual Environments. Pure vision-based tracking has low jitter and high accuracy but cannot guarantee real-time pose recovery under all circumstances. Pure inertial tracking has high update rates and full 6DOF recovery but lacks long-term stability due to sensor noise. In order to overcome the individual drawbacks and to build better tracking system, we introduce the fusion of vision-based and inertial tracking. Sensor fusion makes the proposal tracking system robust, fast, accurate, and low jitter and noise. Hybrid tracking is implemented with Kalman Filter that operates in a predictor-corrector manner. Combining bluetooth serial communication module gives the system a full mobility and makes the system affordable, lightweight energy-efficient. and practical. Full 6DOF recovery and the full mobility of proposal system enable the user to interact with mobile device like PDA and provide the user with natural interface.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.566-569
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• 1993

This paper presents the design and implementation of an industrial controller for an autonomous guided vehicle(AGV) with economic sensor. A guidance scheme provides accurate tracking and achieves faster minimizing oftracking error. A sensor at the center provides the position and orientation of the vehicle relative to the track. Control laws that make use of this information have been devised to achieve accurate and fast tracking. The gains are modified on-line to achieve proper tracking. The simulation and implementation results are provided for the illustration of the implemented controller.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.90-101
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• 2000

In this paper, we propose a controller for differentially steered wheeled mobile robots. The controller uses input-output linearization algorithm and artificial neural network to stabilize the dynamic model and compensate uncertainties. The proposed neural network part has 6 inputs, 1 hidden layer, 2 torque outputs and features fast online learning and good performance on structure error learning basis. Simulation results show that the proposed controller perform precisely tracking of reference path and is robust to uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.194-199
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• 1989

In this paper, using the direct drive arm for plant, the controller is developed to track the desired trajectory in high speed and precision. For the purpose of this, through extending self-tuning pole-placement algorithm, we developed self-tuning pole-shift algorithm which is fast in response and good tracking for the reference tracking change. Developed controller is applied a three-link direct drive arm with the varing payload to track the desired tracking. And, through the computer simulation, the performance of developed controller is compared with the performance of the computed torque method and the self-tuning pole placement algorith.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1491-1494
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• 2002

The paper introduces a novel system of two hands real-time tracking based on the unrestricted hand skin segmentation by multi color systems. After corer-based segmentation and pre-processing operation, a label set of regions is created to locate the two hands automatically. By the normalization, template matching is used to find out the left or right hand. An improved fast self-adaptive tracking algorithm is applied and Canny filter is used for hand detection.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.843-845
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• 1995

There are a variety of trajectory and control algorithms available for robot trajectory tracking. Before using the enhanced trajectory and control algorithms to reduce the tracking error, we introduce the new method which reduces the tracking error by clipping the joint velocity. A lot of robot trajectory tracking methods are proposed to enhance the robot tracking, but irregular tracking errors are always accompanied. Up to now, these irregular tracking errors are gradually but uniformly reduced by introducing more complicated control algorithms. It is intuitively obvious to reduce only the big errors selectively in the irregular ones for the better performance. By heuristic method, big tracking errors in these irregular ones are assumed mostly due to the fast moving of joint with respect to the same tracking and control method. So, in this paper, we introduce a new method which reduce the big tracking errors by clippings the joint velocity with the constraint of given path. Using this method, desired trajectory tracking is obtained within the far reduced error bound. Also, this method is successfully applied to generate the path-constrained error reducing trajectories for 2-axis SCARA type robot.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.6
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• pp.649-654
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• 2009

In this paper, an frequency tracking algorithm for weak signal tracking is proposed. The proposed frequency tracking algorithm uses a FMS (Fast Minus Slow) discriminator for frequency error estimation. This frequency tracking algorithm shows good frequency estimation performance under weak signal condition and is a computationally efficient for embedded software GNSS receiver. The software GNSS receiver implementing the proposed weak signal tracking algorithms could track GPS signal down to - 159dBm signal strength in the signal generator test and real GPS signal under dense urban condition.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.8
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• pp.27-34
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• 2012

This paper proposes variable incremental conductance(IC) algorithm for maximum power point tracking(MPPT) control of photovoltaic. The conventional perturbation & observation(PO) and IC MPPT control algorithm generally uses fixed step size. A small step size reduces a tracking error in the steady state but slows a tracking speed in the transient state. Also, a large step size is fast a tracking speed but increases a tracking error. Therefore, this paper proposes variable IC MPPT algorithm that adjust automatically step size according to operating conditions. To improve a tracking speed and accuracy, when operating point is far from the maximum power point(MPP), the step size uses maximum value and when a operating point is near from the MPP, the step size uses variable step size that adjust according to slope of P-V curve. The validity of MPPT algorithm proposed in this paper prove through compare with conventional PO and IC MPPT algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.839-844
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• 2009

In this paper, a real-time eye tracking method using fast face detection is proposed. Most of the current eye tracking systems have operational limitations due to sensors, complicated backgrounds, and uneven lighting condition. It also suffers from slow response time which is not proper for a real-time application. The tracking performance is low under complicated background and uneven lighting condition. The proposed algorithm detects face region from acquired image using elliptic Hough transform followed by eye detection within the detected face region using Haar-like features. In order to reduce the computation time in tracking eyes, the algorithm predicts next frame search region from the information obtained in the current frame. Experiments through simulation show good performance of the proposed method under various environments.