• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1456-1459
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• 2005

To compensate the drawbacks, a new localization method that estimates the global position of the mobile robot by using a camera set on ceiling in the corridor is proposed. This scheme is not a relative localization, which decreases the position error through algorithms with noisy sensor data. The effectiveness of the proposed localization scheme is demonstrated by the experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.37.1-37
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• 2002

Localization is one of the most important functions for the mobile robot navigating in the unstructured environment. Most of previous localization schemes estimate current position and pose of mobile robot by applying various localization algorithms with the information obtained from sensors which are set on the mobile robot, or by recognizing an artificial landmark attached on the wall, or objects of the environment as natural landmark in the indoor environment. Several drawbacks about them have been brought up. To compensate the drawbacks, a new localization method that estimates the global position of the mobile robot by using a camera set on ceiling in the corridor is proposed. This sch...

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.105-110
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• 1999

This paper presents a local obstacle avoidance method for indoor mobile robots using Lane method and velocity Space Command approach. The method locates local obstacles using the information form multi-sensors, such that ultrasonic sensor array and laser scanning sensor. The method uses lane method to determine optimum collision-free heading direction of a robot. Also, it deals with the robot motion dynamics problem to reduce some vibration and guarantee fast movement as well. It yields translational and rotational velocities required to avoid the detected obstacles and to keep the robot heading direction toward goal location as close as possible. For experimental verification of the method, a mobile robot driven by two AC servo motors, equipped with 24 ultrasonic sensor array and laser scanning sensor navigates using the method through a corridor cluttered with obstacle.

• Korean Journal of Human Ecology
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• v.17 no.5
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• pp.1001-1013
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• 2008

The purpose of this study were to make clear the actual state of indoor air quality by cooling in private institute classrooms and to analyze influencing factors on indoor air quality. The measurements of physical elements and observations of architectural characteristics and living conditions were carried out in each 1 classroom of 5 private institutes. Measuring elements were indoor temperature, relative humidity, $PM_{10}$, HCHO, CO, and $CO_2$ concentration. As results, the averages of indoor temperature each classroom were $21.7\sim28.1^{\circ}C$. 3 classrooms were lower than the Maintenance standard($26\sim28^{\circ}C$) of School Health Law. The means of relative humidity were 48$\sim$63%, all classrooms were ranged within the standard(30$\sim$80%). The means of $PM_{10}$ concentration were 2.1 $\sim$ 17 $\mu g/m^3$, all classrooms were kept within the standard(100 $\mu g/m^3$). The means of HCHO concentration were 0.02$\sim$0.16 ppm, 2 classrooms were exceed the standard(0.1 ppm). The means of CO concentration were 1.4$\sim$3.6 ppm, all classrooms were kept within the standard(10ppm). The means of $CO_2$ concentration were 1,593$\sim$3,819 ppm, all classrooms were exceed the standard(1,000ppm). The results of analysis on influencing factors of the physical elements are as follow; the air conditioner set of temperature, personal necessities like hair spray, teacher's smoking in corridor, windows and doors opening time, the number of students, and volume of classroom.

• Korean Journal of Microbiology
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• v.41 no.3
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• pp.188-194
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• 2005

To assess microbiological indoor air quality in schools, concentrations of viable airborne microorganisms were monitored at classrooms and corridors of 3 middle or high schools in Ulsan. Airborne microorganisms were sampled at various situations during a semester (class-hour, lunchtime, after school) and during a vacation with an impaction-type air sampler. During the semester, the number of bacteria was the highest at lunchtime in corridor with an average of $1,111\;MPN/m^{3}$ and lowest at class-hour in corridor with an average of $132\;MPN/m^{3}$. During the vacation, the bacterial concentrations at classrooms and corridors were only $5{\%}$ and $27{\%}$ of the values during class-hours of the semester, respectively. Among the colonies tested, $60{\%}$ were identified as relatively harmless Micrococcus species and $12{\%}$ were Staphylococcus species. During the semester, the average values of fungal concentrations at each situation ranged from 105 to $213\;MPN/m^{3}$, and the values during the vacation were $32\;MPN/m^{3}$ at classrooms and $83\;MPN/m^{3}$ in corridors. Fungal genera such as Cladosporium, Penicillium, and Aspergillus were identified from the colonies. The obtained data can be considered as a step to set a guideline for bioaerosols in indoor environment of schools.

• Spatial Information Research
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• v.18 no.1
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• pp.77-87
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• 2010

Spatio-temporal join operators are essential to the management of spatio-temporal data such as moving objects. For example, the join operators are parts of processing to analyze movement of objects and search similar patterns of moving objects. Various studies on spatio-temporal join queries in outdoor space have been done. Recently with advance of indoor positioning techniques, location based services are required in indoor space as well as outdoor space. Nevertheless there is no one about processing of spatio-temporal join query in indoor space. In this paper, we introduce continuous spatio-temporal self-join queries in indoor space and propose a method of processing of the join queries over stream data of moving objects. The continuous spatio-temporal self-join query is to update the joined result set satisfying spatio-temporal predicates continuously. We assume that positions of moving objects are represented by symbols such as a room or corridor. This paper proposes a data structure, called Candidate Pairs Buffer, to filter and maintain massive stream data efficiently and we also investigate performance of proposed method in experimental study.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.932-938
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• 2013

Recently, the Fingerprint, which is one of the methods of indoor localization using WLAN, has been many studied owing to robustness about ranging error by the diffraction and refraction of radio waves. However, in the signal gathering process and comparison operation for the measured signals with the database, this method requires time consumption and computational complexity. In order to compensate for these problems, this paper presents, based on proposed modified database, WLAN indoor localization algorithm using selective operation of collected signal in real time. The proposed algorithm reduces the configuration time and the size of the data in the database through linear interpolation and thresholding according to the signal strength, the localization accuracy, while reducing the computational complexity, is maintained through selective operation of the signals which are measured in real time. The experimental results show that the accuracy of localization is improved to 17.8% and the computational complexity reduced to 46% compared to conventional Fingerprint in the corridor by using proposed algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.11 s.114
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• pp.1058-1064
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• 2006

In this paper, the channel capacity of a specified wireless indoor multiple-input multiple-output(MIMO) channel is estimated by analyzing spatial characteristics of this channel using the three-dimensional ray tracing method, and a technique for deriving an optimized separation of multi-antenna elements is proposed. At first, the ray paths, the path losses, and the time-delay profile are computed using the three-dimensional ray tracing method in an indoor corridor environment, which has the line of sight(LOS) and non-line of sight(NLOS) regions. The ray tracing method is verified by a comparison between the computation results and the measurements which are obtained with dipole antennas, an amplifier and a network analyzer. Then, an MIMO system is positioned in the indoor channel environment and the ray paths and path losses are computed for four antenna-position combinations and various values of the antenna separation to obtain the channel capacity for the MIMO system. An optimum antenna-separation is derived by averaging the channel capacities of 100 receiver positions with four different antenna combinations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1339-1355
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• 2023

Localization is a hot research spot for many areas, especially in the mobile robot field. Due to the weak signal of the global positioning system (GPS), the alternative schemes in an indoor environment include wireless signal transmitting and receiving solutions, laser rangefinder to build a map followed by a re-localization stage and visual positioning methods, etc. Among all wireless signal positioning techniques, Wi-Fi is the most common one. Wi-Fi access points are installed in most indoor areas of human activities, and smart devices equipped with Wi-Fi modules can be seen everywhere. However, the localization of a mobile robot using a Wi-Fi scheme usually lacks orientation information. Besides, the distance error is large because of indoor signal interference. Another research direction that mainly refers to laser sensors is to actively detect the environment and achieve positioning. An occupancy grid map is built by using the simultaneous localization and mapping (SLAM) method when the mobile robot enters the indoor environment for the first time. When the robot enters the environment again, it can localize itself according to the known map. Nevertheless, this scheme only works effectively based on the prerequisite that those areas have salient geometrical features. If the areas have similar scanning structures, such as a long corridor or similar rooms, the traditional methods always fail. To address the weakness of the above two methods, this work proposes a coarse-to-fine paradigm and an improved localization algorithm that utilizes Wi-Fi to assist the robot localization in a geometrically similar environment. Firstly, a grid map is built by using laser SLAM. Secondly, a fingerprint database is built in the offline phase. Then, the RSSI values are achieved in the localization stage to get a coarse localization. Finally, an improved particle filter method based on the Wi-Fi signal values is proposed to realize a fine localization. Experimental results show that our approach is effective and robust for both global localization and the kidnapped robot problem. The localization success rate reaches 97.33%, while the traditional method always fails.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1448-1451
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• 2004

Position estimation is one of the most important functions for the mobile robot navigating in the unstructured environment. Most of previous localization schemes estimate current position and pose of mobile robot by applying various localization algorithms with the information obtained from sensors which are set on the mobile robot, or by recognizing an artificial landmark attached on the wall, or objects of the environment as natural landmark in the indoor environment. Several drawbacks about them have been brought up. To compensate the drawbacks, a new localization method that estimates the absolute position of the mobile robot by using a fixed camera on the ceiling in the corridor is proposed. And also, it can improve the success rate for position estimation using the proposed method, which calculates the real size of an object. This scheme is not a relative localization, which decreases the position error through algorithms with noisy sensor data, but a kind of absolute localization. The effectiveness of the proposed localization scheme is demonstrated through the experiments.