• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.932-935
• /
• 1996

This paper proposes position estimation and path-tracking of a wheeled-mobile robot(WMR). Odometry and two distance measuring sensors are used to measure distance between guide wall and body and to locate its own position. And extended Kalman filter is introduced to fusion sensors and reduce noise. State feedback controller using the estimated position and path-tracking miles guidance control system. The computer simulation shows that proposed algorithm is well coincide with theoretical approach.

• Journal of the Korean Institute of Navigation
• /
• v.25 no.4
• /
• pp.361-369
• /
• 2001

This thesis describes the design of a stabilized algorithm for shipboard satellite antenna systems which can enhance the tracking performance. In order to overcome some drawbacks of the conventional step tracking algorithm, the proposed algorithm searches for the best tracking angles using gradient-based formulae and signal intensities measured according to a search pattern. The effectiveness of the proposed algorithm is demonstrated through simulation using real-world data.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10a
• /
• pp.164-168
• /
• 1988

This paper utilizes an optimal control law for the accurate tracking servo system design. The devivation of a simple control law implementing microprocessor is made to minimize position and speed error of the controller. The 16 bit microprocessor receives command angular position and calculate the control algorithm for accurate tracking and provides control system gain scheduling to achieve very short settling time. Simulation results and some experimental results of the position controlled tracking using 4.5Kw DC servo motor are shown.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.558-563
• /
• 1992

Bearing information of target is used critically for target tracking in underwater environment. In passive sonar, target bearing measurements are obtained by processing the acoustic signal emanating from the target. PDA tracking algorithm is usually applied in this case since bearing measurements have several peaks due to interference with other acoustic sources or reflections from underwater media. In this paper, we propose a modified PDA algorithm adopting new probabilistic distributions of the number, position, and amplitude of peaks based on the analysis of real data. This algorithm is tested on real and artificially generated data. The computer simulation result shows improvement of the tracking performance.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.36-40
• /
• 1986

This paper describes a design of the dynamic robot arm controller with two points of view, robustness and minimum tracking error. A new approach to the robust control of robot arm is developed and an explicit solution for minimum tracking error control is obtained from the regulator problem in the error space given by modifying the tracking problem. This control law is applied to the SCARA robot and the computer simulation is presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.179-181
• /
• 1987

In this paper, a self-tuning controller design is proposed by using pole-zero placement method and considering a system time delay. To got better tracking for the generalized self-tuning controller, pole placement method for the closed loop system and zero placement method for the error transfer function are Introduced. The proposed method shows better efficiency than pole placement method for minimizing tracking error. Simulation gives good results in tie reference signal tracking.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.48.2-48
• /
• 2001

This paper deals with robust integral tracking control problem based on Lyapunov method via FL(Feedback Linearization) in order to solve a reference tracking problem of nonlinear system with parameter uncertainties. To overcome a restrictive matching condition the uncertainties is characterized in a suitable form. The design procedure which combine FL and LMIs(Linear Matrix Inequalities) based on Lyapunov method to achieve the robust performance and stability is developed. Finally, the performance of proposed controller is demonstrated via simulation of a linear reference tracking problem in the MLS(Magnetic levitating System).

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
• /
• v.37 no.2
• /
• pp.114-121
• /
• 2011

Introduction: The aim of this study was to demonstrate that the simulation surgery on rapid prototype (RP) model, which is based on the 3-dimensional computed tomography (3D CT) data taken before surgery, has the same accuracy as traditional orthograthic surgery with an intermediate splint, using an optoelectronic tracking navigation system. Materials and Methods: Simulation surgery with the same treatment plan as the Le Fort I osteotomy on the patient was done on a RP model based on the 3D CT data of 12 patients who had undergone a Le Fort I osteotomy in the department of oral and maxillofacial surgery, Seoul National University Dental Hospital. The 12 distances between 4 points on the skull, such as both infraorbital foramen and both supraorbital foramen, and 3 points on maxilla, such as the contact point of both maxillary central incisors and mesiobuccal cuspal tip of both maxillary first molars, were tracked using an optoelectronic tracking navigation system. The distances before surgery were compared to evaluate the accuracy of the RP model and the distance changes of 3D CT image after surgery were compared with those of the RP model after simulation surgery. Results: A paired t-test revealed a significant difference between the distances in the 3D CT image and RP model before surgery.(P<0.0001) On the other hand, Pearson's correlation coefficient, 0.995, revealed a significant positive correlation between the distances.(P<0.0001) There was a significant difference between the change in the distance of the 3D CT image and RP model in before and after surgery.(P<0.05) The Pearson's correlation coefficient was 0.13844, indicating positive correlation.(P<0.1) Conclusion: Theses results suggest that the simulation surgery of a Le Fort I osteotomy using an optoelectronic tracking navigation system I s relatively accurate in comparing the pre-, and post-operative 3D CT data. Furthermore, the application of an optoelectronic tracking navigation system may be a predictable and efficient method in Le Fort I orthognathic surgery.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.9
• /
• pp.1312-1319
• /
• 2022

This paper defines an effectiveness index for optical continuous observation of unknown space objects and presents a range of design variables combinations that can satisfy the effectiveness index from a telescope/mount control system perspective using integrated simulation. The overall system-level simulation was implemented and the tracking performance was analyzed by considering design variables such as target position prediction and frame rate, image processing time and measurement error, target trajectory characteristics, and maneuver performance of mount gimbal. As a result of the analysis, it was confirmed that the continuous tracking performance of the optical observation system is dependent on the combination of frame rate and mount maneuver performance. In a situation where an optical observation system is designed or a similar system is implemented using COTS, an appropriate combination of parameters between design variables can be found through effectiveness analysis simulation as in this study.

• Journal of Korea Multimedia Society
• /
• v.25 no.2
• /
• pp.145-156
• /
• 2022

Nowadays, the complexity of object tracking models among hardware applications has become a more in-demand duty to complete in various indeterminable environment tracking situations with multifunctional algorithm skills. In this paper, we propose a virtual city environment using AirSim (Aerial Informatics and Robotics Simulation - AirSim, CityEnvironment) and use the DQN (Deep Q-Learning) model of deep reinforcement learning model in the virtual environment. The proposed object tracking DQN network observes the environment using a deep reinforcement learning model that receives continuous images taken by a virtual environment simulation system as input to control the operation of a virtual drone. The deep reinforcement learning model is pre-trained using various existing continuous image sets. Since the existing various continuous image sets are image data of real environments and objects, it is implemented in 3D to track virtual environments and moving objects in them.