• KIPS Transactions on Software and Data Engineering
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• v.9 no.3
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• pp.77-82
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• 2020

Most of the navigation in the vehicle has been developed based on a complex structure of PSF(Physical Storage Format) files, making it difficult to support incremental map updates. DB-based navigation is drawing attention as a next-generation navigation method to solve this problem. In DB-based navigation that supports incremental map updates, data fragmentation due to continuous map data updates can increase data access costs, which can lead to a decrease in search performance. In this paper, as one of the performance enhancement methods of DB-based navigation that supports incremental map updates, data fragmentation prevention techniques were presented and the performance improvement effect was verified through actual implementation.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.709-715
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• 2010

This paper represents a map building and localization system for mobile robot. Map building and navigation is a complex problem because map integrity cannot be sustained by odometry alone due to errors introduced by wheel slippage, distortion and simple linealized odometry equation. For accurate localization, we propose sensor fusion system using encoder sensor and indoor GPS module as relative sensor and absolute sensor, respectively. To build a map, we developed a sensor based navigation algorithm and grid based map building algorithm based on Embedded Linux O.S. A wall following decision engine like an expert system was proposed for map building navigation. We proved this system's validity through field test.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.643-645
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• 2000

This paper puts emphasis on navigation in virtual environment, which is one of the major interfaces for the interactivity between human and virtual environment in virtual reality circumstances and worlds. It proposes a new navigation method: 2d Map-Based navigation, which prevents user's spatial lost in 3D Virtual Environment. The 2D Map-Based Navigation is composed of three major processes, Constant Velocity Navigation, Collision Detection and Avoidance, and Path Adjustment. The 2D Map-Based Navigation can reduce user's difficulties and improve user's sense of presence and reality in the virtual environments. The experiment study proved that the 2D Map-Based Navigation is a very natural, straightforward and useful navigation interface in the virtual environment.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1189-1195
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• 2008

We introduce a MEMS-based pedestrian dead reckoning (PDR) system. A walking navigation algorithm for pedestrians is presented and map-matching algorithm for the navigation system based on dead reckoning (DR) is proposed. The PDR is equipped on the human body and provides the position information of pedestrians. And this is able to be used in ubiquitous sensor network (USN), U-hearth monitoring system, virtual reality (VR) and etc. The PDR detects a step using a novel technique and simultaneously estimates step length. Also an azimuth of the pedestrian is calculated using a fluxgate which is the one of magnetometers. Map-matching algorithm can be formulated to integrate the positioning data with the digital road network data. Map-matching algorithm not only enables the physical location to be identified from navigation system but also improves the positioning accuracy. However most of map-matching algorithms which are developed previously are for the car navigation system (CNS). Therefore they are not appropriate to implement to pedestrian navigation system based on DR system. In this paper, we propose walking navigation system and map-matching algorithm for PDR.

• Korean Journal of Computational Design and Engineering
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• v.19 no.3
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• pp.272-280
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• 2014

Most of the car navigation systems pzrovide 2D or 3D virtual map-based driving guidance. One of the important issues is how to reduce cognitive burden to the driver who should interpret the abstracted information to real world driving information. Recently, an augmented reality (AR)-based navigation is considered as a new way to reduce cognitive workload by superimposing guidance information into the real world scene captured by the camera. In particular, head-up display (HUD) is popular to implement AR navigation. However, HUD is too expensive to be set up in most cars so that the HUD-based AR navigation is currently unrealistic for navigational assistance. Meanwhile, smartphones with advanced computing capability and various sensors are popularized and also provide navigational assistance. This paper presents a research on cognitive effect and responsiveness of an AR navigation by a comparative study with a conventional virtual map-based navigation on the same smartphone. This paper experimented both quantitative and qualitative studies to compare cognitive workload and responsiveness, respectively. The number of eye gazing at the navigation system is used to measure the cognitive effect. In addition, questionnaires are used for qualitative analysis of the responsiveness.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.4
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• pp.87-97
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• 2012

A knowledge map is a diagramed network among knowledge which is related with each other in terms of the referential navigation. To formally as well as structurely represent various contextual use of knowledge, the ontology technology has been recommended to be applied. This research proposes a methodology to build the ontology-based knowledge map promoting referential navigation between knowledge. To prove the validity of the proposed concepts, an ontology-based knowledge map is designed as an example, which demonstrates whether the designed knowledge network in the knowledge map is underpinned by the referential navigation between knowledge.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.169-176
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• 2009

Low-cost sensors have been widely used for mobile robot navigation in recent years. However, navigation performance based on low-cost sensors is not good enough to be practically used. Among many navigation techniques, building of an accurate map is a fundamental task for service robots, and mapping with low-cost IR sensors was investigated in this research. The robot's orientation uncertainty was considered for mapping by modifying the Bayesian update formula. Then, the data association scheme was investigated to improve the quality of a built map when the robot's pose uncertainty was large. Six low-cost IR sensors mounted on the robot could not give rich data enough to align the range data by the scan matching method, so a new sample-based method was proposed for data association. The real experiments indicated that the mapping method proposed in this research was able to generate a useful map for navigation.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.117-124
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• 2006

In this paper, we develope the navigation system for patrol robots in indoor environment. The proposed system consists of PDA map modelling, a localization algorithm based on a global position sensor and an automatic charging station. For the practical use in security system, the PDA is used to build object map on the given indoor map. And the builded map is downloaded to the mobile robot and used in path planning. The global path planning is performed with a localization sensor and the downloaded map. As a main controller, we use PXA270 based hardware platform in which embedded linux 2.6 is developed. Data handling for various sensors and the localization algorithm are performed in the linux platform. Also, we implemented a local path planning algorithm for object avoidance with ultra sonar sensors. Finally, for the automatic charging, we use an infrared ray system and develop a docking algorithm. The navigation system is experimented with the two-wheeled mobile robot using North-Star localization system.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.2
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• pp.101-107
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• 2014

Mobile robots use an environment map of its workspace to complete the surveillance task. However grid-based maps that are commonly used map format for mobile robot navigation use a large size of memory for accurate representation of environment. In this reason, grid-based maps are not suitable for path planning of mobile robots using embedded board. In this paper, we present the path planning algorithm that produce a secure path rapidly. The proposed approach utilizes a hybrid map that uses less memory than grid map and has same efficiency of a topological map. Experimental results show that the fast path planning uses only 1.5% of the time that a grid map based path planning requires. And the results show a secure path for mobile robot.

• Knowledge Management Research
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• v.13 no.1
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• pp.1-12
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• 2012

A knowledge map is a network-typed diagram visualizing all kinds of knowledge that influences each other to solve a problem. A knowledge map determines the structure of knowledge categorizing and archiving by defining the relationship of referential navigation among knowledge. Since tremendous and increasing number of knowledge needs to be included in a knowledge map, a knowledge map must be organized automatically by considering the contents and relationships of knowledge. This paper suggests the concept and prototype of a semi-automated knowledge map which automatically maps new piece of knowledge onto a manually provided draft map. The prototype knowledge map is based on the recursive programming to make a knowledge map automatically determine the location of the newly-entered knowledge by considering the referential relationship between knowledge. The proposed knowledge enables the knowledge network to expand autonomously by automatically including and storing knowledge. Also, it can improve the accuracy and applicability of knowledge for problem-solving, because the relationship of referential navigation among knowledge can be efficiently and effectively expressed.