• 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.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.216-224
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• 2014

This paper compares methods for attitude estimation of a UUV(Unmanned Underwater Vehicle). Attitude estimation plays a key role in underwater navigation using DVL(Doppler Velocity Log). The paper proposes attitude estimation methods using EKF(Extended Kalman Filter), UKF(Unscented Kalman Filter), and CF(Complementary Filter). It derives methods using the measurements from MEMS-AHRS(Microelectromechanical Systems-Attitude Heading Reference System) and DVL. The methods are used for navigation in a test pool and their navigation performance is compared. The results suggest that even if there is no measurement relative to some absolute landmarks, DVL-only navigation can be useful for navigation in a limited time and range.

• The Journal of Korea Robotics Society
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• v.9 no.3
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• pp.160-169
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• 2014

Odometry using wheel encoder is a common relative positioning technique for wheeled mobile robots. The major drawback of odometry is that the kinematic modeling errors are accumulated when the travel distance increases. Therefore, accurate calibration of odometry is required. In several related works, various schemes for odometry calibration are proposed. However, design guidelines of test tracks for odometry calibration were not considered. More accurate odometry calibration results can be achieved by using appropriate test track because the position and orientation errors after the test are affected by the test track. In this paper, we propose the design guidelines of test tracks for odometry calibration schemes using experimental heading errors. Numerical simulations and experiments clearly demonstrate that the proposed design guidelines result in more accurate calibration results.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.577-583
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• 2007

Simultaneous Localization and Mapping (SLAM) is the process of building a map of an unknown environment and simultaneously localizing a robot relative to this map. SLAM is very important for the indoor navigation of a mobile robot and much research has been conducted on this subject. Although feature-based SLAM using an Extended Kalman Filter (EKF) is widely used, it has shortcomings in that the computational complexity grows in proportion to the square of the number of features. This prohibits EKF-SLAM from operating in real time and makes it unfeasible in large environments where many features exist. This paper presents an algorithm which reduces the computational complexity of EKF-SLAM by using topological information (TI) extracted through a thinning process. The global map can be divided into local areas using the nodes of a thinning-based topological map. SLAM is then performed in local instead of global areas. Experimental results for various environments show that the performance and efficiency of the proposed EKF-SLAM/TI scheme are excellent.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.483-488
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• 2008

An active omni-directional raging system using an omni-directional vision with structured light has many advantages compared to the conventional ranging systems: robustness against external illumination noise because of the laser structured light and computational efficiency because of one shot image containing $360^{\circ}$ environment information from the omni-directional vision. The omni-directional range data represents a local distance map at a certain position in the workspace. In this paper, we propose a matching algorithm for the local distance map with the given global map database, thereby to localize a mobile robot in the global workspace. Since the global map database consists of line segments representing edges of environment object in general, the matching algorithm is based on relative position and orientation of line segments in the local map and the global map. The effectiveness of the proposed omni-directional ranging system and the matching are verified through experiments.

• Genomics & Informatics
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• v.7 no.2
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• pp.131-135
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• 2009

Domains are the building blocks of proteins. Exon shuffling is an important mechanism accounting for combination of a limited repertoire of protein domains in the evolution of multicellular species. A relative excess of domains encoded by symmetric exons in metazoan phyla has been presented as evidence of exon shuffling, and symmetric domains can be divided into old and new domains by determining the ages of the domains. In this report, we compare the spread, versatility, and subcellular localization of old and new domains by analyzing eight metazoan genomes and their respective annotated proteomes. We found that new domains have been expanding as multicellular organisms evolved, and this expansion was principally because of increases in class 1-1 domains amongst several classes of domain families. We also found that younger domains have been expanding in membranes and secreted proteins along with multi-cellular organism evolution. In contrast, old domains are located mainly in nuclear and cytoplasmic proteins. We conclude that the increasing mobility and versatility of new domains, in contrast to old domains, plays a significant role in metazoan evolution, facilitating the creation of secreted and transmembrane multidomain proteins unique to metazoa.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.418-421
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• 1988

Holographic interferometry is applied in dental research to study the motion of teeth and the deformation of the associated facial structure. We consider double exposure holographic interferometry which has limiting factors such as the stability of fringes, the recording time, the amount of exposure, the localization of fringes and sensitivity. These factors are taken into account to make interferogram. The resulting interferogram gives fringe pattern which is analyzed qualitatively to determine the relative rotation and the deformation of the facial structure.

• Animal cells and systems
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• v.2 no.3
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• pp.395-401
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• 1998

The regional distribution and relative frequency of endocrine cells were studied immunohistochemically in the gastrointestinal tract (GIT) of the Manchurian chipmunk, Tamias sibiricus asiaticus. Six kinds of endocrine cells were identified in this study. 5-hydroxytryptamine (5-HT)-immunoreactive cells were detected throughout the GIT. These cells were observed in moderate numbers in the pylorus, duodenum, jejunum, ileum, fundus, colon, and rectum. Somatostatin- and bovine pancreatic polypeptide (BPP)-immunoreactive cells were also identified throughout the GIT. The former were abundant in the pylorus region while the latter were scattered In ileum and colon. Motilin-immunoreactive cells were rarely detected in the small intestine. A few neurotensin-immunoreactive cells were detected in jejunum, ileum and colon. Also, a few substance P-immunoreactive cells were observed to be restricted to duodenum and jejunum.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.883-887
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• 2016

Navigating an unknown environment is a challenging task for a robot, especially when a large number of obstacles exist and the odometry lacks reliability. Pose tracking allows the robot to determine its location relative to its previous location. The ICP (iterative closest point) has been a powerful method for matching two point clouds and determining the transformation matrix between the maps. However, in a situation where odometry is not available and the robot moves far from its original location, the ICP fails to calculate the exact displacement. In this paper, we suggest a method that is able to match two different point clouds taken a long distance apart. Without using any odometry information, it only exploits the features of corner points containing information on the surroundings. The algorithm is fast enough to run in real time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.55-57
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• 2018

In Simultaneous Localization and Mapping (SLAM), the robot acquire its map of environment while simultaneously localize itself relative to the map. Now a day, a map acquired by the mobile robots limit to specific area, in an indoor environment and cannot able to navigate autonomous between different floors. We propose a design that could able to overcome this issue in order to navigate multiple floors with one end goal mission to a target destination in the course of autonomous navigation. In this research, we consider all the floors have identical structural arrangement. Internet of Things (IoT) playing crucial role in bridging between "things" and Robot Operating System (ROS) enabled mobile robots.