• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.467-470
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• 2003

When user wants to find objects which have the nearest position from him, we use the nearest neighbor (NN) query. The GIS applications, such as navigation system and traffic control system, require processing of NN query for moving objects (MOs). MOs have trajectory with changing their position over time. Therefore, we should be able to find NN object continuously changing over the whole query time when process NN query for MOs, as well as moving nearby on trajectory of query. However, none of previous works consider trajectory information between objects. Therefore, we propose a method of continuous NN query for trajectory of MOs. We call this CTNN (continuous trajectory NN) technique. It ran find constantly valid NN object on the whole query time by considering of trajectory information.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1419-1423
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• 2004

In this paper, we propose an algorithm for planning an optimal path to capture a moving object by a mobile robot in real-time. The direction and rotational angular velocity of the moving object are estimated using the Kalman filter, a state estimator. It is demonstrated that the moving object is tracked by using a 2-DOF active camera mounted on the mobile robot and then captured by a mobile manipulator. The optimal path to capture the moving object is dependent on the initial conditions of the mobile robot, and the real-time planning of the robot trajectory is definitely required for the successful capturing of the moving object. Therefore the algorithm that determines the optimal path to capture a moving object depending on the initial conditions of the mobile robot and the conditions of a moving object is proposed in this paper. For real-time implementation, the optimal representative blocks have been utilized for the experiments to show the effectiveness of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.186-190
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• 2003

In this paper, we propose an algorithm for planning an optimal path to capture a moving object by a mobile robot in real-time. The direction and rotational angular velocity of the moving object are estimated using the Kalman filter, a state estimator. It is demonstrated that the moving object is tracked by using a 2-DOF active camera mounted on the mobile robot and then captured by a mobile manipulator. The optimal path to capture the moving object is dependent on the initial conditions of the mobile robot, and the real-time planning of the robot trajectory is definitely required for the successful capturing of the moving object. Therefore the algorithm that determines the optimal path to capture a moving object depending on the initial conditions of the mobile robot and the conditions of a moving object is proposed in this paper. For real-time implementation, the optimal representative blocks have been utilized for the experiments to show the effectiveness of the proposed algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.85-90
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• 2017

Various mobile devices are spreading in recent developments in mobile computing environments. Especially the popularity of mobile devices equipped with GPS has become widespread, and various application services utilizing location information are born. In this paper, we propose a system model for storing and managing the trajectory of moving objects, which is the set of location information of moving objects acquired in continuous time, and the UDF (User-Defined Functions) based trajectory index method which can quickly query the large data set of moving object and the Pre-Materialized table method. Then we compare and evaluate the performance of each method through experiments. Experimental results show that the Pre-Materialized table method is about 1.2 times faster than the UDF based trajectory index method on execution time.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2357-2359
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• 1998

This paper proposes trajectory tracking of the moving object based on one camera vision system. And, this system proposes a method which robot manipulator grips moving object and predicts coordinate of moving objcet. The trajectory tracking and position coordinate are computed by vision data acquired to camera. Robot manipulator tracks and grips moving object by vision data. The proposed vision systems use a algorithm to do real-time processing.

• Journal of Korea Multimedia Society
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• v.7 no.5
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• pp.617-632
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• 2004

Video Data includes moving objects which change spatial positions as time goes by. In this paper, we propose a new modeling method for a moving object contained in the video data. In order to effectively retrieve moving objects, the proposed modeling method represents the spatial position and the size of a moving object. It also represents the visual features and the trajectory by considering direction, distance and speed or moving objects as time goes by. Therefore, It allows various types of retrieval such as visual feature based similarity retrieval, distance based similarity retrieval and trajectory based similarity retrieval and their mixed type of weighted retrieval.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.183-189
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• 2009

Recently, PCS, PDA and mobile devices, such as the proliferation of spread, GPS (Global Positioning System) the use of, the rapid development of wireless network and a regular user even images, audio, video, multimedia data, such as increased use is for. In particular, video data among multimedia data, unlike the moving object, text or image data that contains information about the movements and changes in the space of time, depending on the kinds of changes that have sigongganjeok attributes. Spatial location of objects on the flow of time, changing according to the moving object (Moving Object) of the continuous movement trajectory of the meeting is called, from the user from the database that contains a given query trajectory and data trajectory similar to the finding of similar trajectory Search (Similar Sub-trajectory Retrieval) is called. To search for the trajectory, and these variations, and given the similar trajectory of the user query (Tolerance) in the search for a similar trajectory to approximate data matching (Approximate Matching) should be available. In addition, a large multimedia data from the database that you only want to be able to find a faster time-effective ways to search different from the existing research is required. To this end, in this paper effectively divided into a grid to search for the trajectory to the trajectory of moving objects, similar to the effective support of the search trajectory offers a new grid-based search techniques.

• Spatial Information Research
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• v.19 no.2
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• pp.57-64
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• 2011

This paper describes how to storing and querying trajectory information on PostgreSQL/PostGIS. Recently as technology of mobile devices is advancing, many researches for location-based services and moving object's trajectory have been studied. Trajectory is the set of information of the location by the time, and is one of the most im portant information for location-based services. Traditional spatial database systems do not support trajectory data types and functions. In this paper, we propose a trajectory data type and query functions for moving objects on PostgreSQL/PostGIS.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.33-38
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• 2019

Recently, to support location-based services, there have been many researches which consider the spatial network. For this, there are many experimental data for data processing on the road network. However, the data to process the trajectory of moving objects are not suitable. Therefore, we propose index structure to process the trajectory data on the road network and the trajectory data generation algorithm. In addition, to prove efficiency of our index structure and algorithm, we show that edge-based trajectory data are generated through the proposed algorithm using the map data of San Francisco Bay.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.741-748
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• 2001

In this paper, we propose a method of tracking and capturing a moving object by a mobile robot. The position of the moving object is acquired from the relation through color-based image information from a 2-DOF active camera mounted on the mobile robot. The direction and rotational angular velocity of the moving object are estimated using a state estimator. A Kalman fiber is used as the state estimator for taking characteristics of robustness against noises and uncertainties included in the input data. After estimating the trajectory of the moving object, we decide on the optimal trajectory and plan the motion of the mobile robot to capture the target object within the shortest distance and time. The effectiveness of the proposed method is demonstrated by the simulations and experiments.