• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.23-25
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• 2010

In this paper, we studied linking method for updating navigation map with new address map. This method is hierarchical as we chose candidate using attribute data for geometry matching. Limiting a matching range, we conducted a experiment ICP with geometry matching. As a result, for linking method it's quite satisfied but for updating method, we decided that we have to do more precise method for updating.

• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.421-423
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• 2003

3D 가상환경 개발 초기 단계에서부터 효과적인 Navigation을 위해서 Navigation Aid에 대한 연구가 꾸준히 진행되어왔다. 그러나 지금까지는 환경 구조의 중요 지점만을 정리한 요약 형태의 정보를 제공하는 방법이 주를 이루고 있어서, Navigation 대상 환경에 익숙지 않은 사용자에게 환경구조를 이해하게 하는 인지적 부담을 주고 있다. 본 논문에서는 사용자의 Navigation을 위한 인지적 부담을 최소화 하는 토픽맵을 적용한 투어코스 자동생성 및 생성보조 시스템을 본 Navigation Aid 시스템이 적용된 가상 환경을 통해서 제안했다. 이는 현실세계에 존재하는 환경을 가상환경을 통해 사전방문 하거나 효과적인 이동경로를 선정하는데 도움을 줄 수 있을 것으로 기대한다.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.83-91
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• 2011

The roadmap DB update for unknown roads is a very important factor for car navigation systems. In this paper, we propose a cloud computing based roadmap generation method for use between heterogeneous navigation system for unknown roads. While the drivers drive on unknown roads, the proposed method extracts the road attribute information, and then generates the metadata in an XML format that is available for the heterogeneous navigation systems in a cloud environment. The metadata is proposed to be used as a replacement for conventional proprietary roadmap formats which used by roadmap providers, which is efficient for heterogeneous navigation system providers in a cloud computing environment. Then, this metadata is provided to the roadmap DB providers through the cloud computing interfaces. With the proposed method, the roadmap DB providers update the own roadmap DB for navigation systems in real time. Therefore, the proposed method can reduce the costs of an actual traveling test and the maintenance for the roadmap DB provides. Thus, the cloud-oriented road map generation method can more efficiently update the unknown road information.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.262-265
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• 2008

We design level 1 traffic thematic map for common data structure. Level 1 means the road that can passing cars. If public office and private company use this form, they can save amount of money from overlapping update. And widely use of traffic analysis, navigation and traffic information system. For design common data structure we compared several data structure(traffic thematic map, ITS standard node/link, Car navigation map), and generalization these characteristic data. After generalization we considered about application parts. It can use of public part(traffic analysis, road management, accident management) and private part(car navigation, map product, marketing by variable analysis) etc.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.203-209
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• 2010

This paper presents a hierarchical fuzzy motion planner for humanoid robots in 3D uneven environments. First, we define both motion primitives and locomotion primitives of humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the workspace. We use a passage map, an obstacle map and a gradient map of obstacles to distinguish obstacles. A mid-level planner creates subgoals that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. We use a local obstacle map to find the subgoals along the global path. A low-level planner searches for an optimal sequence of locomotion primitives between subgoals by using fuzzy motion planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.451-459
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• 2011

Fundamentally, there are 5 systems are needed for autonomous navigation of unmanned ground vehicle: Localization, environment perception, path planning, motion planning and vehicle control. Path planning and motion planning are accomplished based on result of the environment perception process. Thus, high reliability of localization and the environment perception will be a criterion that makes a judgment overall autonomous navigation. In this paper, via map matching using vehicle dynamic model and LIDAR sensors, replace high price localization system to new one, and have researched an algorithm that lead to robust autonomous navigation. Finally, all results are verified via actual unmanned ground vehicle tests.

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.140-148
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• 2012

For autonomous navigation, map, pose tracking, and finding the shortest path are required. Because there is no GPS signal in indoor environment, the current position should be recognized in the 3D map by using image processing or something. In this paper, we explain 3D map creation technology by using depth camera like Kinect and pose tracking in 3D map by using 2D image taking from camera. In addition, the mechanism of avoiding obstacles is discussed.

• 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.