• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.103-111
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• 2023

Mountains area, especially walking in open space is important for special active field which is based on mountain terrain. Recent research on pedestrian-path includes elements about pedestrian and various environment by analyzing network, but it is mainly focusing on limited space except for data-poor terrain like a mountain terrain. This paper proposes an architecture to generate walking path considering the slope for mountain terrain open space through virtual network made of mesh. This architecture shows that it reflects real terrain more effective when measuring distance using slope and is possible to generate mountain walking path using open space unlike other existing services, and is verified through the test. The proposed architecture is expected to utilize for pedestrian-path generation way considering mountain terrain open space in case of distress, mountain rescue and tactical training and so on.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.37-44
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• 2012

There are approximately 25,724 shelters to which people can be quickly evacuated for safety in case of emergency across the nation, and Seoul has about 3,870 shelters. Those nationwide shelters are located at a point within a five-minute radius for quick evacuation. Seoul's shelter capacity can hold 285% of its population. The problem is, however, that there is no knowing how many shelters are reachable within five minutes when considering walking speed according to individual differences in age, height, health state, and physical condition. In addition, available service areas become different according to the spatial allocation and distribution of shelters with possible vulnerable points. This study thus defined the pedestrian walking speed at 1m/s, 1.3m/s, and 2m/s by reviewing previous studies and conducted network analysis of the Location Allocation Model with the designated shelters and road networks in Seoul. The results identified the shelter service and vulnerable areas in each administrative district of Seoul according to walking speeds. It was analyzed that the vulnerable areas in which the elderly could not reach a shelter were more than twice as big as those of adult men and women with a fast walking speed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.249-256
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• 2016

Recently, a number of techniques to ensure the free walking for the visually impaired and transportation vulnerable have been studied. As a device for free walking, there are such as a smart cane and smart glasses to use the computer vision, ultrasonic sensor, acceleration sensor technology. In a typical technique, such as techniques for finds object and detect obstacles and walking area and recognizes the symbol information for notice environment information. In this paper, we studied recognization algorithm of the selected symbols that are required to visually impaired, with the deep learning algorithm. As a results, Use CNN(Convolutional Nueral Network) technique used in the field of deep-learning image processing, and analyzed by comparing through experimentation with various deep learning architectures.

• Spatial Information Research
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• v.19 no.1
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• pp.83-91
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• 2011

The route finding analysis is an essential geo-related decision support tool in a LBS(Location based Services) and previous researches related to route guidance have been mainly focused on route guidances for vehicles. However, due to the recent spread of personal computing devices such as PDA, PMP and smart phone, route guidance for pedestrians have been increasingly in demand. The pedestrian route guidance is different from vehicle route guidance because pedestrians are affected more surrounding environment than vehicles. Therefore, pedestrian path finding needs considerations of factors affecting walking. This paper aimed to extract factors affecting walking and charting the factors for application factors affecting walking to pedestrian path finding. In this paper, we found various factors about environment of road for pedestrian and extract the factors affecting walking. Factors affecting walking consist of 4 categories traffic, sidewalk, network, safety facility. We calculated weights about each factor using analytic hierarchy process (AHP). Based on weights we calculated scores about each factor's attribute. The weight is maximum score of factor. These scores of factor are used to optimal pedestrian path finding as path finding cost with distance, accessibility.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.4
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• pp.399-408
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• 2023

In this paper, we propose a solution that enables continuous indoor/outdoor positioning of smartphone users through the integration of Pedestrian Dead Reckoning (PDR) and GPS/WiFi signals. Considering that accurate step detection affects the accuracy of PDR, we propose a Deep Neural Network (DNN)-based technology to distinguish between walking and non-walking signals such as walking in place. Furthermore, in order to integrate PDR with GPS and WiFi signals, a technique is used to select a proper measurement by distinguishing between indoor/outdoor environments based on GPS Dilution of Precision (DOP) information. In addition, we propose a technology to adaptively change the measurement error covariance matrix by detecting measurement outliers that mainly occur in the indoor/outdoor transition section through a residual-based χ² test. It is verified through experiments on a testbed that these technologies significantly improve the performance of PDR and PDR/GPS/WiFi fingerprinting-based integrated pedestrian navigation.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.6
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• pp.3-14
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• 2018

The aim of this study is to propose a method for calculating the weight of walking energy in ERAM model by calculating it for the analysis of vertical and horizontal spaces in a building. Conventional theories on the space analysis in the field of architectural planning predict the pedestrian volume of network spaces in urban street or in two-dimensional plane within a building, however, for vertical and horizontal spaces in a building, estimates of the pedestrian volume by those theories are limited. Because in the spatial syntax and ERAM model have been applied weights such as the spatial depth, adjacent angles, and physical distances available only to the two-dimensional same layer or plane. Therefore, the following basic assumptions and analysis conditions in this study were established for deriving a predictor of pedestrian volume in vertical and horizontal spaces of a building. The basic premise of space analysis is not to address the relationship between the pedestrian volume and the spatial structure itself but to the properties of spatial structure connection that human beings experience. The analysis conditions in three-dimensional spaces are as follows : 1) Measurement units should be standardized on the same scale, and 2) The connection characteristics between spaces should influence the accessibility of human beings. In this regard, a factor of walking energy has the attributes to analyze the connection of vertical and horizontal spaces and satisfies the analysis conditions presented in this study. This study has two implications. First, this study has shown how to quantitatively calculate the walking energy after a factor of walking energy was derived to predict the pedestrian volume in vertical and horizontal spaces. Second, the method of calculating the walking energy can be applied to the weights of the ERAM model, which provided the theoretical basis for future studies to predict the pedestrian volume of vertical and horizontal spaces in a building.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.67-74
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• 2011

In recent years, with increasing utilization of mobile devices such as smartphones, the need for PNS(Pedestrian Navigation Systems) that provide guidance for moving pedestrians is increasing. For the navigation services, road network is the most important component when it comes to creating route and guidance information. In particular, pedestrian network requires modeling methods for more detailed and vast space compared to road network. Therefore, more efficient method is needed to establish pedestrian network that was constructed by existing field survey and manual editing process. This research proposed a pedestrian network creation method appropriate for pedestrians, based on CNS(Car Navigation Systems) data that already has been broadly constructed. Pedestrian network was classified into pedestrian link(sidewalk, side street, walking facility) and openspace link depending on characteristics of walking space, and constructed by applying different methodologies in order to create path that similar to the movements of actual pedestrians. The proposed algorithm is expected to become an alternative for reducing the time and cost of pedestrian network creation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.114.5-114
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• 2001

In this paper, the model for personal navigation system using low-cost inertial sensors and error compensation method with GPS are proposed. Simulation is accomplished for the performance test. WNS(Walking Navigation System) is a kind of personal navigation using the number of a walk, stride and azimuth. Because the accuracy of these variables determines the navigational performance, computational methods have been investigated. The step is detected using the motion pattern by walking motion, stride is determined by neural network and azimuth is calculated with gyro´s output. The neural network filters off unnecessary motions. However, error compensation method is needed, because the error of navigation information increases with time ...

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1228-1230
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• 1996

A neural network(NN) mechanism is proposed to modify the gait of a biped robot that walks on sloping surface using sensory inputs. The robot starts walking on a surface with no priori knowledge of the inclination of the surface. By accumulating experience during walking, the robot improves its walking gait and finally forms a gait that is adapted to the surface inclination. A neural controller is proposed to control the gait which has 72 reciprocally inhibited and excited neurons. PI control is used for position control, and the neurons are trained by a reinforcement learning mechanism. Experiments of static gait learning and pseudo dynamic learning are performed to show the validity of the proposed reinforcement learning mechanism.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1539-1543
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• 2004

This paper describes platform overview, system integration and dynamic walking control of the humanoid robot, KHR-2 (KAIST Humanoid Robot - 2). We have developed KHR-2 since 2003. KHR-2 has totally 41 DOF (Degree Of Freedom). Each arm including a hand has 11 DOF and each leg has 6 DOF. Head and trunk also has 6 DOF and 1 DOF respectively. In head, two CCD cameras are used for eye. In order to control all joints, distributed control architecture is adopted to reduce the computation burden of the main controller and to expand the devices easily. The main controller attached its back communicates with sub-controllers in real-time by using CAN (Controller Area Network) protocol. We used Windows XP as its OS (Operating System) for fast development of main control program and easy extension of peripheral devices. And RTX, HAL(Hardware Abstraction Layer) extension program, is used to realize the real-time control in Windows XP environment. We present about real-time control of KHR-2 in Windows XP with RTX and basic walking control algorithm. Details of the KHR-2 are described in this paper.