• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1046-1052
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• 2016

For the safe driving of autonomous vehicles, accurate position estimation is required. Generally, position error must be less than 1m because of lane keeping. However, GPS positioning error is more than 1m. Therefore, we must correct this error and a map matching algorithm is generally used. Especially, road marking intensity map have been used in many studies. In previous work, 3D LIDAR with many vertical layers was used to generate a local intensity map. Because it can be obtained sufficient longitudinal information for map matching. However, it is expensive and sufficient road marking information cannot be obtained in rush hour situations. In this paper, we propose a localization algorithm using an accumulated intensity local map. An accumulated intensity local map can be generated with sufficient longitudinal information using 3D LIDAR with a few vertical layers. Using this algorithm, we can also obtain sufficient intensity information in rush hour situations. Thus, it is possible to increase the reliability of the map matching and get accurate position estimation result. In the experimental result, the lateral RMS position error is about 0.12m and the longitudinal RMS error is about 0.19m.

• Journal of Korean Society of Rural Planning
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• v.17 no.3
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• pp.91-101
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• 2011

The purpose of this study is to suggest a landscape resources evaluation strategy of rural waterfront villages along the river. This strategy consists of three phases: 1) an evaluation of rural amenity landscape resources, 2) an evaluation of water landscape resources, and 3) development of a positioning map based on the results of phase 1) and 2) the study result as follows. First, the evaluation method used in phase 1) was modified as a set of proposed evaluation indicators to assess development potential on rural waterfront villages. Second, to evaluate water landscape resources in rural waterfront villages, a series of evaluation index was developed including water area, diversity of water resources, biodiversity, and landscape quality. And the last, the positioning map showed relative position of waterfront villages obtained from two evaluation results: rural amenity landscape resources and water landscape resources. The study examined the proposed strategy as a possible alternative to evaluate landscape quality to 398 rural waterfront villages along the Han River. Landscape resources evaluation strategy proposed here could contribute to government officials and planners to operate systematic planning and management of rural waterfront villages.

• KIISE Transactions on Computing Practices
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• v.23 no.2
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• pp.110-115
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• 2017

We propose a new indoor positioning algorithm named Cut-off algorithm. This algorithm cuts off candidates of beacons and reference points in advance, before looking for K neighbor reference points which are guessed to be closest to the user's actual location. The algorithm consists of two phases: off-line phase, and on-line phase. In the off-line phase, RSSI and UUID data from beacons are gathered at reference points placed in the indoor environment, and construct a fingerprint map of the data. In the on-line phase, the map is reduced to a smaller one according to the RSSI data of beacons received from the user's device. The nearest K reference points are selected using the reduced map, which are used for estimating user's location. In both phases, relative ranks of the peak signals received from each beacon are used, which smoothen the fluctuations of the signals. The algorithm is shown to be more efficient in terms of accuracy and estimating time.

• Journal of the Korean Society of Costume
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• v.66 no.7
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• pp.50-68
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• 2016

The objectives of this study are to identify the self-image and preferred fashion styles that Korean career women seek in different daily situations, and to propose a positioning map in accords with the findings. The study conducted a survey and in-depth interviews. The study used twenty items of self-image adjectives extracted from existing studies, and eighteen fashion style stimuli collected by examining women's wear brands. The study surveyed 329 career women. Their daily situation was classified into five situations; external meeting and presentation, ordinary work, wedding and family gathering, blind date or date, and meeting with friends and acquaintances. The analysis results of this study showed that self-image and fashion style preferences are relevant to daily situation. The image most sought in external meetings and presentation was the 'Elegant' image, and the image most sought in meetings with friends and acquaintances was the 'active' image. Women on dates or blind dates sought the 'feminine' image the most, however they preferred to avoid this image during external meetings and presentations. Among fashion styles, the 'elegant/classic' style was most preferred, and the 'sexy/avant-garde' style had the lowest preference among all the styles. 'Mannish' was preferred in ordinary work and meeting with friends and acquaintances, however, it was shown as having the lowest preference level in blind dates or dates. The 'romantic/natural' style was highly preferred in meeting with friends and acquaintances, however it had a low level of preference for external meetings and presentations. This study has significance in providing practical information to utilize in fashion industry by identifying the relationship between self-image and preferred fashion style sought by career women according to daily situation, and using the results to propose a positioning map.

• Journal of Platform Technology
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• v.11 no.5
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• pp.97-103
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• 2023

Unlike GPS, which is an outdoor positioning technology that is universally and uniformly used all over the world, various technologies are still being developed in the field of indoor positioning technology. In order to acquire accurate indoor location information, a standard of representative indoor positioning technology is required. Recently, indoor positioning technology is expanding into the Real Time Location Service (RTLS) area based on high-precision location data. Accordingly, a new type of indoor positioning technology is being proposed. Thanks to the development of artificial intelligence, artificial intelligence-based indoor positioning technology using wireless signal data of a smartphone is rapidly developing. At this time, in the process of collecting data necessary for artificial intelligence learning, data that is distorted or inappropriate for learning may be included, resulting in lower indoor positioning accuracy. In this study, we propose a data preprocessing technology for artificial intelligence learning to obtain improved indoor positioning results through the refinement process of the collected data.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.961-966
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• 2012

In this paper, we analyze a main patent positioning to analyze data based on patent application as stage of data collection to organize knowledge map of LED through patent application. We also analyze the present condition of patent application for technology sector. We propose basic data to make knowledge map through the analysis of technical distribution for applicant by each country.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.256-262
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• 2004

A key component of an autonomous mobile robot is to localize itself and build a map of the environment simultaneously. In this paper, we propose a vision-based localization and mapping algorithm of mobile robot using fisheye lens. To acquire high-level features with scale invariance, a camera with fisheye lens facing toward to ceiling is attached to the robot. These features are used in mP building and localization. As a preprocessing, input image from fisheye lens is calibrated to remove radial distortion and then labeling and convex hull techniques are used to segment ceiling and wall region for the calibrated image. At the initial map building process, features we calculated for each segmented region and stored in map database. Features are continuously calculated for sequential input images and matched to the map. n some features are not matched, those features are added to the map. This map matching and updating process is continued until map building process is finished, Localization is used in map building process and searching the location of the robot on the map. The calculated features at the position of the robot are matched to the existing map to estimate the real position of the robot, and map building database is updated at the same time. By the proposed method, the elapsed time for map building is within 2 minutes for 50㎡ region, the positioning accuracy is ±13cm and the error about the positioning angle of the robot is ±3 degree for localization.

• Culinary science and hospitality research
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• v.22 no.5
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• pp.37-51
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• 2016

The purposes of this study were (1) to investigate the important selection attributes of coffee brands and the relative positions of major coffee brands on the positioning map through similarities and preferences of coffee brands that customers perceive and (2) to provide Korean coffee brands with strategic information about how to differentiate themselves from existing competitors in the Chinese market. A total of 268 samples were used for data analysis that comprised frequency analysis, descriptive statistics, ALSCAL, and regression analysis. The results showed that among 8 coffee brand selection attributes the most important was atmosphere, followed by cleanness and sanitary condition, and convenient location and transportation. Friendly service, taste of coffee, price and variety of menu were next and brand was the least important among 8 selection attributes. The results of positioning map showed that Maan Coffee was evaluated the highest iin atmosphere, cleanness and sanitary condition, and convenient location and transportation compared to other coffee brands. Marketing strategies for Korean coffee franchisers (Angel-in-us Coffee and Caffe Bene) were provided for successful repositioning in the Beijing coffee market.

• Journal of IKEEE
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• v.9 no.1 s.16
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• pp.7-18
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• 2005

A key component of an autonomous mobile robot is to localize itself accurately and build a map of the environment simultaneously. In this paper, we propose a vision-based mobile robot localization and mapping algorithm using scale-invariant features. A camera with fisheye lens facing toward to ceiling is attached to the robot to acquire high-level features with scale invariance. These features are used in map building and localization process. As pre-processing, input images from fisheye lens are calibrated to remove radial distortion then labeling and convex hull techniques are used to segment ceiling region from wall region. At initial map building process, features are calculated for segmented regions and stored in map database. Features are continuously calculated from sequential input images and matched against existing map until map building process is finished. If features are not matched, they are added to the existing map. Localization is done simultaneously with feature matching at map building process. Localization. is performed when features are matched with existing map and map building database is updated at same time. The proposed method can perform a map building in 2 minutes on $50m^2$ area. The positioning accuracy is ${\pm}13cm$, the average error on robot angle with the positioning is ${\pm}3$ degree.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10c
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• pp.397-399
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• 2003

2001년 이후 Car Navigation System(이하 CNS)을 장착한 차량이 급증하는 가운데 많은 기업들이 차량의 위치 오차를 최소화 시키는 노력에 힘쓰고 있다. 본 논문은 CNS에서 발생되는 차량의 위치 오차를 최소화하기 위한 일환으로 GPS(Global Positioning System) 위성으로부터 계산되어진 차량의 위치 좌표와 차량의 실제(true) 좌표간의 오차를 보정하여 디스플레이(display) 상의 오류를 방지할 수 있는 맵매칭(map­matching)방법을 제시한다.