• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.747-752
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• 1998

Ultrasonic sensors have been widely used to recognize the working environment for a mobile robot. However, their intrinsic problems, such as specular reflection, wide beam angle, and slow propagation velocity, require an excessive number of sensors to be integrated for achieving the sensing goal. This paper proposes a new measurement scheme which uses only two sets of ultrasonic sensors to determine the location and the type of a target surface. By measuring the time difference between the returned signals from the target surface, which are generated by two transmitters with 1 ㎳ difference, it classifies the type and determines the size of the target surface. Since the proposed sensor system uses only two sets of ultrasonic sensors to recognize and localize the target surface, it significantly simplifies the sensing system and reduces the signal processing time so that the working environment can be recognized in real time.

• ETRI Journal
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• v.41 no.4
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• pp.483-493
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• 2019

Considering the high dimensions of video sequences, it is often challenging to acquire a sufficient dataset to train the tracking models. From this perspective, we propose to revisit the idea of hand-crafted feature learning to avoid such a requirement from a dataset. The proposed tracking approach is composed of two phases, detection and tracking, according to how severely the appearance of a target changes. The detection phase addresses severe and rapid variations by learning a new appearance model that classifies the pixels into foreground (or target) and background. We further combine the raw pixel features of the color intensity and spatial location with convolutional feature activations for robust target representation. The tracking phase tracks a target by searching for frame regions where the best pixel-level agreement to the model learned from the detection phase is achieved. Our two-phase approach results in efficient and accurate tracking, outperforming recent methods in various challenging cases of target appearance changes.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.890-900
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• 2016

This paper presents a multiple target tracking system using target feature information. In the proposed system, the state of target is defined as its kinematic as well as feature : the kinematic includes a location and a velocity; the feature contains the image correlation between a prior target and a current measurement. The feature information is used for generating the validation matrix and association probability of joint probabilistic data association (JPDA) algorithm. Through the Kalman filter, the target kinematic is updated. Then the tracking information is cycled by the track management algorithm. The system has been evaluated using the images obtained from Electro-Optics/ InfraRed (EO/IR) sensor. It is verified that the proposed system can reduce the complexity burden of JPDA process and can enhance the track maintenance rate.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.8 no.3
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• pp.132-137
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• 2009

In this paper, a position recognition system is designed, implemented, and tested using IEEE 802.15.4a PHY (CSS) hardware and Tiny OS environment. The system is designed with extensibility and flexibility. The system consists of five kinds of nodes which have different functions from each other. Three communication channels are used for collision avoidance. In each cell, an arbiter node is used to minimize message collisions. The proposed arbitration protocol is designed to support mobility of arbitrary target nodes. Target nodes calculates their locations with communications to four location reference nodes which are placed on the comers of each cell.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.279-290
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• 2010

Technical countermeasures against debris flow should be established upon the risk level of the target location. Risk of debris flow should consider the hazard imposed by debris flow and vulnerability of the facilities to debris flow. In this research, we have defined the target location for risk evaluation and suggested scoring method of hazard of debris flow and vulnerability of road to debris flow. By defining risk rank into 6 categories in terms of possibility of damage during rainfall and using the risk scores of 46 debris flow cases, we have suggested risk ranking matrix. The method can be used in ranking the drainage basin adjacent to road by simply determining the hazard with vulnerability score and can be used for planning the debris flow countermeasures.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.210-216
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• 2017

In the paper we propose and implement a new indoor localization system where the techniques of magnetic field based fingerprinting and pedestrian dead reckoning are combined. First, we determine a target's location by comparing acquired magnetic field values with a magnetic field map containing pre-collected field values at different locations and choosing the location having the closest value. As the target moves, we use pedestrian dead reckoning to estimate the expected moving path, reducing the maximum positioning error of the initial location. The system eliminates the problem of localization error accumulation in pedestrian dead reckoning with the help of the fingerprinting and does not require Wi-Fi AP infrastructure, enabling cost-effective localization solution.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.2
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• pp.187-194
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• 2015

Accurate relative location estimation is a key requirement in indoor localization systems based on wireless sensor networks (WSNs). However, although these systems have applied not only various optimization algorithms but also fusion with sensors to achieve high accuracy in position determination, they are difficult to provide accurate relative azimuth and locations to users because of cumulative errors in inertial sensors with time and the influence of external magnetic fields. This paper based on ultra-wideband positioning system, which is relatively suitable for indoor localization compared to other wireless communications, presents an indoor localization system for estimating relative azimuth and location of location-unaware nodes, referred to as target nodes without applying any algorithms with complex variable and constraints to achieve high accuracy. In the proposed method, the target nodes comprising three mobile nodes estimate the relative distance and azimuth from two reference nodes that can be installed by users. In addition, in the process of estimating the relative localization information acquired from the reference nodes, positioning errors are minimized through a novel modified rounding estimation technique in which Kalman filter is applied without any time consumption algorithms. Experimental results show the feasibility and validity of the proposed system.

• Journal of KIBIM
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• v.7 no.1
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• pp.45-53
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• 2017

Continuous research efforts have been made on acquiring location data on construction sites. As a result, GPS and RFID are increasingly employed on the site to track the location of equipment and materials. However, these systems are based on radio frequency technologies which require attaching tags on every target entity. Implementing the systems incurs time and costs for attaching/detaching/managing the tags or sensors. For this reason, efforts are currently being made to track construction entities using only cameras. Vision-based 3D tracking has been presented in a previous research work in which the location of construction manpower, vehicle, and materials were successfully tracked. However, the proposed system is still in its infancy and yet to be implemented on practical applications for two reasons. First, it does not involve entity matching across two views, and thus cannot be used for tracking multiple entities, simultaneously. Second, the use of a checker board in the camera calibration process entails a focus-related problem when the baseline is long and the target entities are located far from the cameras. This paper proposes a vision-based method to track multiple workers simultaneously. An entity matching procedure is added to acquire the matching pairs of the same entities across two views which is necessary for tracking multiple entities. Also, the proposed method simplified the calibration process by avoiding the use of a checkerboard, making it more adequate to the realistic deployment on construction sites.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3_1spc
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• pp.607-614
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• 2013

This paper proposes a robot driving system and sensor implementation for use with an education robot. This robot has multiple functions and was designed so that children could use it with interest and ease. The robot recognizes the location of a user and follows that user at a specific distance when the robot and user communicate with each other. In this work, the robot was designed and manufactured to evaluate its performance. In addition, an embedded board was installed with the purpose of communicating with a smart phone, and a camera mounted on the robot allowed it to monitor the environment. To allow the robot to follow a moving user, a set of sensors combined with an RF module and ultrasonic sensors were adopted to measure the distance between the user and the robot. With the help of this ultrasonic sensors arrangement, the location of the user couldbe identified in all directions, which allowed the robot to follow the moving user at the desired distance. Experiments were carried out to see how well the user's location could be recognized and to investigate how accurately the robot trackedthe user, which eventually yielded a satisfactory performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1611-1629
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• 2016

Recently, deploying WiFi access points (APs) for facilitating indoor localization has attracted increasing attention. However, most existing mechanisms in this aspect are typically simulation based and further they did not consider how to jointly utilize pre-existing APs in target environment and newly deployed APs for achieving high localization performance. In this paper, we propose a measurement-based AP deployment mechanism (MAPD) for placing APs in target indoor environment for assisting fingerprint based indoor localization. In the mechanism design, MAPD takes full consideration of pre-existing APs to assist the selection of good candidate positions for deploying new APs. For this purpose, we first choose a number of candidate positions with low location accuracy on a radio map calibrated using the pre-existing APs and then use over-deployment and on-site measurement to determine the actual positions for AP deployment. MAPD uses minimal mean location error and progressive greedy search for actual AP position selection. Experimental results demonstrate that MAPD can largely reduce the localization error as compared with existing work.