• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.38.3-38
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• 2002

$\textbullet$ The topological map using a thinning needs much simpler computation than that using a Voronoi. $\textbullet$ A thinning can provide much information on the environment (additional nodes). $\textbullet$ Each node created in a local map is considered as temporary and redundant nodes are discarded. $\textbullet$ A global topological map can be built fast and correctly through a thinning algorithm. $\textbullet$ Path planning can be easily achieved with a topological map.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.817-822
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• 2004

This paper provides a global path planning method using self-organizing feature map which is a method among a number of neural network. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.293-297
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• 2021

This paper presents how to create a 3D map and solve problems related to generating a global path planning for navigation. Map creation and localization were performed using the RTAB-Map package to create a 3D map of the environment. In addition, when the target point is within the obstacle space, the problem of not generating a global path was solved using the asr_navfn package. The performance of the proposed system is validated through experiments with a wheelchair-type robot.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.458-459
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• 2009

This global case study pursues diversification and intensification for an application system of the national wind map which has been developed to support national strategy building and promotion of wind energy dissemination. We chose nine counties' national wind maps and compared their map area, extraction height, temporal and spatial resolution, download services, etc. to derive a best practice for the Korea wind map application system. Therefore, the application system are designed to offer high resolution height information of which covers wind turbine rotor sweeping area and time-series dataset which can be downloaded for further analysis by users. It is anticipated that the system would contribute greatly to wind energy policy, business and research sectors once the derived ideas have been implemented to the application system

• ETRI Journal
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• v.36 no.6
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• pp.913-923
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• 2014

This paper proposes a global mapping algorithm for multiple robots from an omnidirectional-vision simultaneous localization and mapping (SLAM) approach based on an object extraction method using Lucas-Kanade optical flow motion detection and images obtained through fisheye lenses mounted on robots. The multi-robot mapping algorithm draws a global map by using map data obtained from all of the individual robots. Global mapping takes a long time to process because it exchanges map data from individual robots while searching all areas. An omnidirectional image sensor has many advantages for object detection and mapping because it can measure all information around a robot simultaneously. The process calculations of the correction algorithm are improved over existing methods by correcting only the object's feature points. The proposed algorithm has two steps: first, a local map is created based on an omnidirectional-vision SLAM approach for individual robots. Second, a global map is generated by merging individual maps from multiple robots. The reliability of the proposed mapping algorithm is verified through a comparison of maps based on the proposed algorithm and real maps.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.275-281
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• 2007

This paper presents a motion planning strategy for legged robots using locomotion primitives in the complex 3D environments. First, we define configuration, motion primitives and locomotion primitives for legged robots. A hierarchical motion planning method based on a combination of 2.5 dimensional maps of the 3D workspace is proposed. A global navigation map is obtained using 2.5 dimensional maps such as an obstacle height map, a passage map, and a gradient map of obstacles to distinguish obstacles. A high-level path planner finds a global path from a 2D navigation map. A mid-level planner creates sub-goals that help the legged robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local obstacle map that describes the edge or border of the obstacles is used to find the sub-goals along the global path. A low-level planner searches for a feasible sequence of locomotion primitives between sub-goals. We use heuristic algorithm in local motion planner. The proposed planning method is verified by both locomotion and soccer experiments on a small biped robot in a cluttered environment. Experiment results show an improvement in motion stability.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.2
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• pp.180-187
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• 2010

In this paper, a global path generation method is suggested using multiple grid maps connected with the mission type of unmanned combat vehicle(UCV). In order to carry out a mission for UCV, it is essential to find a global path which is coincident with the characteristics of the mission. This can be done by considering various combat circumstances represented as grid maps such as velocity map, threat map and communication map. Cost functions of multiple grid maps are linearly combined and normalized to them simultaneously for the path generation. The proposed method is realized using $A^*$, a well known search algorithm, and cost functions are normalized in the ratio of the traverse time which is one of critical information should be provided with the operators using the velocity map. By the experiments, it is checked found global paths match with the mission type by reflecting input data of grid maps properly and the computation time is short enough to regenerate paths in real time as combat circumstances change.

• Investigative Magnetic Resonance Imaging
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• v.22 no.1
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• pp.37-49
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• 2018

Purpose: The effect of global inhomogeneity on quantitative susceptibility mapping (QSM) was investigated. A technique referred to as Simultaneous Unwrapping Phase with Error Recovery from inhomogeneity (SUPER) is suggested as a preprocessing to QSM to remove global field inhomogeneity-induced phase by polynomial fitting. Materials and Methods: The effect of global inhomogeneity on QSM was investigated by numerical simulations. Three types of global inhomogeneity were added to the tissue susceptibility phase, and the root mean square error (RMSE) in the susceptibility map was evaluated. In-vivo QSM imaging with volunteers was carried out for 3.0T and 7.0T MRI systems to demonstrate the efficacy of the proposed method. Results: The SUPER technique removed harmonic and non-harmonic global phases. Previously only the harmonic phase was removed by the background phase removal method. The global phase contained a non-harmonic phase due to various experimental and physiological causes, which degraded a susceptibility map. The RMSE in the susceptibility map increased under the influence of global inhomogeneity; while the error was consistent, irrespective of the global inhomogeneity, if the inhomogeneity was corrected by the SUPER technique. In-vivo QSM imaging with volunteers at 3.0T and 7.0T MRI systems showed better definition in small vascular structures and reduced fluctuation and non-uniformity in the frontal lobes, where field inhomogeneity was more severe. Conclusion: Correcting global inhomogeneity using the SUPER technique is an effective way to obtain an accurate susceptibility map on QSM method. Since the susceptibility variations are small quantities in the brain tissue, correction of the inhomogeneity is an essential element for obtaining an accurate QSM.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.333-336
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• 2000

In this paper, a profile management system consisting of global and local range finders is presented for the automat ion of material pile handling. A global range finder detects range data of the front part of the piles of material and a profile map is obtained from a 3D profile detection algorithm. A local range finder attached on the side of the arm of the reclaimer detects range data with the handling function dynamically, and a local profile patch is acquired from the range data A yard profile map manager constructs a map by using the 3D profile of the global range finder and revises the map by replacing it with the local profile patch obtained Iron the local range finder. The developed vision system was applied to a simulator and the results of test show that it is appropriate to use for automating the material handling.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.337-338
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• 2009