• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.740-744
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• 2008

In this paper, we propose a new time-to-go estimation filter for PN guided missiles. The proposed estimator is derived based on the approximation of the length of the PNG homing trajectory that we newly introduced using the special coordinate system. The coordinate system is convenient for taking the target movement into account. In addition, compared with the previous time-to-go estimation techniques, the parameters required for evaluating the length can be obtained only with the seeker measurements. Moreover, the seeker measurement error statistics can effectively be considered since our filter is derived based on the Kalman filter theory. Simulation result for a typical anti-ship see-skimming missile homing trajectory shows the excellent performance of the proposed filter.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.277-279
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• 2022

Rapid Development and adoption of AIS as a survailance tool has resulted in widespread application of data analysis technology, in addition to AIS ship trajectory clustering. AIS data-based clustering has become an increasingly popular method for marine traffic pattern recognition, ship route prediction and anomaly detection in recent year. In this paper we propose a route waypoint extraction by clustering ships CoG variance trajectory using Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm in both port approach channel and coastal waters. The algorithm discovers route waypoint effectively. The result of the study could be used in traffic route extraction, and more-so develop a maritime anomaly detection tool.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.641-646
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• 2010

This paper presents algorithms for real-time navigation of a humanoid robot with a stereo vision but no other sensors. Using the algorithms, a robot can recognize its 3D environment by retrieving SIFT features from images, estimate its position through the Kalman filter, and plan its path to reach a destination avoiding obstacles. Our approach focuses on estimating the robot’s central walking path trajectory rather than its actual walking motion by using an approximate model. This strategy makes it possible to apply mobile robot localization approaches to humanoid robot localization. Simple collision free path planning and motion control enable the autonomous robot navigation. Experimental results demonstrate the feasibility of our approach.

• Spatial Information Research
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• v.21 no.6
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• pp.57-67
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• 2013

GPS based car navigation systems show significant problems in such environment as a tunnel, a road surrounded by high buildings. In this study, we thus propose a method to determine positions and attitudes using only in-vehicle sensory data without a GPS. To check the feasibility of this method, we constructed a system to acquire in-vehicle sensory data and reference data simultaneously. We acquired test data using this system, estimated the trajectory based on the proposed method and evaluated the accuracy of both the sensory data and the trajectory. The speed and angular velocities provided by the in-vehicle sensors include 1.1 km/h and 0.8 deg/s RMS errors, respectively. The estimated trajectory using these data shows 20.8 m RMS errors for a 15 minute drive. In future, if we further combine additional sensors such as a camera and a GPS, we can achieve a high accurate navigation system at a low cost without an expensive high-grade external IMU.

• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.162-170
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• 2003

In this paper, we propose a robust controller for trajectory control of n-link robot manipulators using feature based on visual feedback. In order to reduce tracking error of the robot manipulator due to parametric uncertainties, integral action is included in the dynamic control part of the inner control loop. The desired trajectory for tracking is generated from feature extraction by the camera mounted on the end effector. The stability of the robust state feedback control system is shown by the Lyapunov method. Simulation and experimental results on a 5-link robot manipulator with two degree of freedom show that the proposed method has good tracking performance.

• Journal of Advanced Navigation Technology
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• v.10 no.2
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• pp.113-120
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• 2006

In this paper, a vision-based robust controller for tracking the desired trajectory a robot manipulator is proposed. The trajectory is generated to move the feature point into the desired position which the robot follows to reach to the desired position. To compensate the parametric uncertainties of the robot manipulator which contain in the control input, the robust controller is proposed. In addition, if there are uncertainties in the Jacobian, to compensate it, a vision-based robust controller which has control input is proposed as well in this paper. The stability of the closed-loop system is shown by Lyapunov method. The performance of the proposed method is demonstrated by simulations and experiments on a two degree of freedom 5-link robot manipulators.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.497-502
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• 2015

One of the goals in the field of mobile robotics is the development of personal service robots for the elderly which behave in populated environments. In this paper, we describe a security robot system and ongoing research results that minimize the risk of the elderly and the infirm to access an area to enter restricted areas with high potential for falls, such as stairs, steps, and wet floors. The proposed robot system surveys a potential falling area with an equipped laser scanner sensor. When it detects walking in elderly or infirm patients who in restricted areas, the robot calculates the velocity vector, plans its own path to forestall the patient in order to prevent them from heading to the restricted area and starts to move along the estimated trajectory. The walking human is assumed to be a point-object and projected onto a scanning plane to form a geometrical constraint equation that provides position data of the human based on the kinematics of the mobile robot. While moving, the robot continues these processes in order to adapt to the changing situation. After arriving at an opposite position to the human's walking direction, the robot advises them to change course. The simulation and experimental results of estimating and tracking of the human in the wrong direction with the mobile robot are presented.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.427-433
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• 2019

This paper propose a fuzzy inference model for map building and navigation for a mobile robot with an active camera, which is intelligently navigating to the goal location in unknown environments using sensor fusion, based on situational command using an active camera sensor. Active cameras provide a mobile robot with the capability to estimate and track feature images over a hallway field of view. In this paper, instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. Command fusion method is used to govern the robot navigation. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of active camera sensor for navigation experiments are fused into the identification process. Navigation performance improves on that achieved using fuzzy inference alone and shows significant advantages over command fusion techniques. Experimental evidences are provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the active camera and the feature images.

• Advances in aircraft and spacecraft science
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• v.6 no.5
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• pp.391-407
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• 2019

Flight trajectory optimization has become an important factor not only to reduce the operational costs (e.g.,, fuel and time related costs) of the airliners but also to reduce the environmental impact (e.g.,, emissions, contrails and noise etc.) caused by the airliners. So far, these factors have been dealt with in the context of 2D and 3D trajectory optimization, which are no longer efficient. Presently, the 4D trajectory optimization is required in order to cope with the current air traffic management (ATM). This study deals with a cubic spline approximation method for solving 4D trajectory optimization problem (TOP). The state vector, its time derivative and control vector are parameterized using cubic spline interpolation (CSI). Consequently, the objective function and constraints are expressed as functions of the value of state and control at the temporal nodes, this representation transforms the TOP into nonlinear programming problem (NLP). The proposed method is successfully applied to the generation of a minimum length optimal trajectories along 4D waypoints, where the method generated smooth 4D optimal trajectories with very accurate results.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.239-246
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• 2004

In this paper, we develop and implement a high integrity GNC(Guidance, Navigation, and Control) system, based on the combined use of the Global Positioning System (GPS) and an Inertial Measurement Unit (IMU), for autonomous land vehicle applications. This paper highlights guidance for the predetermined trajectory and navigation with detection of possible faults during the fusion process in order to enhance the integrity of the navigation loop. The implementation of the GNC system to the autonomous land vehicle presented with fault detection methodology considers high frequency faults from the GPS receiver caused by shadowing and multipath error The implementation, based on a low-cost, strapdown INS aided by standard GPS technology, is described. The results of the field test in the urban environment are presented and showed effectiveness of the GNC system.