• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2450-2452
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• 2004

Map building is essential to a mobile robot navigation system. Localization and path planning methods depend on map building strategies. A topological map is commonly constructed using the GVG(Generalized Voronoi Graph). The advantage of the GVG based topological map is compactness. But the GVG method have many difficulties because it consists of collision-free path. In this paper, we proposed an extended map building method, the AVG (Areal Voronoi Graph) based topological map. The AVG based topological map consists of collision-free area. This feature can improve map building, localization and path planning performance.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.96-103
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• 2014

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.

• ETRI Journal
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• v.40 no.4
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• pp.446-457
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• 2018

Robot navigation allows robot mobility. Therefore, mobility is an area of robotics that has been actively investigated since robots were first developed. In recent years, interest in personal service robots for homes and public facilities has increased. As a result, robot navigation within the home environment, which is an indoor environment, is being actively investigated. However, the problem with conventional navigation algorithms is that they require a large computation time for their building mapping and path planning processes. This problem makes it difficult to cope with an environment that changes in real-time. Therefore, we propose a humanoid robot navigation algorithm consisting of an image processing and optimization algorithm. This algorithm realizes navigation with less computation time than conventional navigation algorithms using map building and path planning processes, and can cope with an environment that changes in real-time.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.104-110
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• 2014

Mapping is a fundamental element for robotic services. There are available many types of map data representation such as grid map, metric map, topology map, etc. As more robots are deployed for services, more chances of exchanging map data among the robots emerge and standardization of map data representation (MDR) becomes more valuable. Currently, activities in developing MDR standard are underway in IEEE Robotics and Automation Society. The MDR standard is for a common representation and encoding of the two-dimensional map data used for navigation by mobile robots. The standard focuses on interchange of map data among components and systems, particularly those that may be supplied by different vendors. This paper aims to introduce MDR standard and its application to map merging. We have applied the basic structure of the MDR standard to a grid map and Voronoi graph as a kind of topology map and performed map merging between two different maps. Simulation results show that the proposed MDR is suitable for map data exchange among robots.

• Journal of the Ergonomics Society of Korea
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• v.29 no.5
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• pp.771-782
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• 2010

Today, the number of elderly drivers who use navigation is increasing with the growing number of elderly drivers. The purpose of this study is to provide guidelines on the interface of car navigation for elderly users. To extract significant factors which were distinguished between young and elderly users, both young and elderly users executed the driving test by installing two car navigation alternatives. The analysis was conducted through t-test. The results show that significantly different factors were the number and the meaning of the menu items in the initial screen, the location and the meaning of the menu icons in the map screen, the ease of search of the menu and the text size in the menu screen. Improvements for the factors of the initial screen and map screen were made with reference to ergonomic guidelines, and suggested through experiments comparing design alternatives for the menu screen. Design alternatives were made through a combination of investigative variables, and the analysis was conducted through ANOVA. The results show that Alternative 7 (the location of the tab was placed at the bottom, menu representation was done with the text font size of 18pt and the location of menu navigation icons was shown at the upper left) was preferred in terms of user's preference and the execution time. So if the suggested menu for elderly users are added to the existing design, both users will satisfy their desires. The guidelines suggested in this study will help the designer of car navigation take elderly users into consideration.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.98.4-98
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• 2002

$\textbullet$ Feature Detection $\textbullet$ Extracting Feature information $\textbullet$ Feature Map $\textbullet$ Feature Map Building $\textbullet$ Experimental Results

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.12
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• pp.577-582
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• 2002

The objective of this paper is to produce a weighted graph map for path-planning of an autonomous mobile robot(AMR) based on the measurements from a single ultrasonic sensor, which are acquired when the autonomous mobile robot explores unknown indoor circumstance. The AMR navigates in th unknown space by following the wall and gathers the range data using the ultrasonic sensor, from which the occupancy grid map is constructed by associating the range data with occupancy certainties. Then, the occupancy grid map is converted to a weighted graph map suing morphological image processing and thinning algorithms. the path- planning for autonomous navigation of a mobile robot can be carried out based on the occupancy grid map. These procedures are implemented and tested using an AMR, and primary results are presented in this paper.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.1
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• pp.102-110
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• 2000

This paper presents an algorithm of local map building for autonomous robot navigation using LASER range finder information. We develop a model of sensor output for a LASER range finder, and obtain an output data of the LASER range finder for a given environment. From the output data, a local map is obtained through the following procedures: (1) filtering of output data to remove noisy and unnecessary data, (2) comparison of filtered data with the original data to restore useful data, (3) thickening of the map obtained from the restored data, and (4) skeletonizing of the thickened map to get a final local map. Through some simulation studies, a map is obtained from the LASER range finder information for a given indoor environment, and is compared with the environment.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.242-249
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• 2014

By a SLAM (simultaneous localization and mapping) method, we get a map of an environment for autonomous navigation of a robot. In this case, we want to know how accurate the map is. Or we want to know which map is more accurate when different maps can be obtained by different SLAM methods. So, several methods for map comparison have been studied, but they have their own drawbacks. In this paper, we propose a new method which compares the accuracy or error of maps relatively and quantitatively. This method sets many corresponding points on both reference map and SLAM map, and computes the translational and rotational values of all corresponding points using least-squares solution. Analyzing the standard deviations of all translational and rotational values, we can know the error of two maps. This method can consider both local and global errors while other methods can deal with one of them, and this is verified by a series of simulations and real world experiments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.666-669
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• 2000

Localization is the process of aligning the robot's local coordinates with the global coordinates of a map. A mobile robot's location is basically computed by a dead reckoning scheme, but this position information becomes increasingly inaccurate during navigation due to odometry errors. In this paper, the method of building a map of a robot's environment using ultrasonic sensor data and the occupancy grid map scheme is briefly presented. Then, the search and matching algorithms to compensate for the odometry error by comparing the local map with the reference map are proposed and verified by experiments. It is shown that the compensated error is not accumulated and exists within the limited range.