• Proceedings of the KIEE Conference
• /
• 2003.07d
• /
• pp.2372-2374
• /
• 2003

With 3-D vision measuring, camera calibration is necessary to calculate parameters accurately. Camera calibration was developed widely in two categories. The first establishes reference points in space, and the second uses a grid type frame and statistical method. But, the former has difficulty to setup reference points and the latter has low accuracy. In this paper we present an algorithm for camera calibration using perspective ratio of the grid type frame with different line widths. It can easily estimate camera calibration parameters such as focal length, scale factor, pose, orientations, and distance. But, radial lens distortion is not modeled. The advantage of this algorithm is that it can estimate the distance of the object. Also, the proposed camera calibration method is possible estimate distance in dynamic environment such as autonomous navigation. To validate proposed method, we set up the experiments with a frame on rotator at a distance of 1,2,3,4[m] from camera and rotate the frame from -60 to 60 degrees. Both computer simulation and real data have been used to test the proposed method and very good results have been obtained. We have investigated the distance error affected by scale factor or different line widths and experimentally found an average scale factor that includes the least distance error with each image. It advances camera calibration one more step from static environments to real world such as autonomous land vehicle use.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.1
• /
• pp.99-107
• /
• 2014

In this paper, a landmark based localization system using a Kinect sensor is proposed and evaluated with the implemented system for precise and autonomous navigation of low cost robots. The proposed localization method finds the positions of landmark on the image plane and the depth value using color and depth images. The coordinates transforms are defined using the depth value. Using coordinate transformation, the position in the image plane is transformed to the position in the body frame. The ranges between the landmarks and the Kinect sensor are the norm of the landmark positions in body frame. The Kinect sensor position is computed using the tri-lateral whose inputs are the ranges and the known landmark positions. In addition, a new matching method using the pin hole model is proposed to reduce the mismatch between depth and color images. Furthermore, a height error compensation method using the relationship between the body frame and real world coordinates is proposed to reduce the effect of wrong leveling. The error analysis are also given to find out the effect of focal length, principal point and depth value to the range. The experiments using 2D bar code with the implemented system show that the position with less than 3cm error is obtained in enclosed space($3,500mm{\times}3,000mm{\times}2,500mm$).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.199-202
• /
• 2009

The optimal path on real road network has been changed by traffic flow of roads frequently. Therefore a path finding system to find the optimal path on real network should consider traffic flow of roads that is changed on real time. The most of existing path finding methods do not consider traffic flow of roads and do not also perform efficiently if they use traffic information. In this paper, we propose an abstraction method of real road network based on the Terminal Based Navigation System (TBNS) with technique such as TPEG. TBNS can be able to provides quality of path better than before as using traffic information that is transferred by TPEG. The proposed method is to abstract real network as simple graph in order to use traffic information. It is composed boundary nodes based on real nodes, all boundary nodes that have the same of connection are merged together. The result of path finding on an abstract graph diminishes the search space.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.245-248
• /
• 2009

Recently, Many studies have been progressing to path-finding with dynamic information on the Terminal Based Navigation System(TBNS). However, the most of existing algorithms are based on $A{\ast}$ algorithm. Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost in case of that there is no way determined by heuristic function or there are 2 way more which have almost same cost. In this paper, two abstract graph(AG) that are different method of construction, Homogeneous Node merging($AG^H$) and Connected Node Merging($AG^C$), are implemented. The abstract graph is a simple graph of real road network. The method of using the abstract graph is proposed for reducing dependency of heuristic and exploring cost. In result of evaluation of performance, $AG^C$ has better performance than $AG^H$ at construction cost but $AG^C$ has worse performance than $AG^H$ exploring cost.

• The Journal of Korean Institute of Information Technology
• /
• v.17 no.10
• /
• pp.57-63
• /
• 2019

Motion errors which are caused by several reasons, non-ideal path, errors of navigation systems, and radar system errors, have to be corrected. Motion compensation methods can compensate the motion error, but not exactly. To correct these residual errors, several autofocus methods are invented. A popular method is phase gradient autofocus (PGA). PGA does not assume specific circumstances, such as isolated point targets and shapes of errors. PGA is an iterative and adaptive method, so that the processing time is the main problem for the real time processing. In this paper, the improved method to select targets for PGA is proposed to reduce processing time. The variances of image pixels are used to select targets with high SNR. The processing of PGA with these targets diminishes the processing time and iterations effectively. The processed results with real radar data, obtained by flight tests, show that the proposed method compensates errors well, and reduce working time.

• Tunnel and Underground Space
• /
• v.32 no.3
• /
• pp.231-242
• /
• 2022

In this study, we developed a robot operating system (ROS)-based autonomous driving robot that estimates the robot's position in underground mines and drives and returns through multiple waypoints. Autonomous driving robots utilize SLAM (Simultaneous Localization And Mapping) technology to generate global maps of driving routes in advance. Thereafter, the shape of the wall measured through the LiDAR sensor and the global map are matched, and the data are fused through the AMCL (Adaptive Monte Carlo Localization) technique to correct the robot's position. In addition, it recognizes and avoids obstacles ahead through the LiDAR sensor. Using the developed autonomous driving robot, experiments were conducted on indoor experimental sites that simulated the underground mine site. As a result, it was confirmed that the autonomous driving robot sequentially drives through the multiple waypoints, avoids obstacles, and returns stably.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.11
• /
• pp.4084-4104
• /
• 2021

Visual place recognition (VPR) is a fundamental yet challenging task of mobile robot navigation and localization. The existing VPR methods are usually based on some pairwise similarity of image descriptors, so they are sensitive to visual appearance change and also computationally expensive. This paper proposes a simple yet effective four-step method that achieves adaptive convolutional neural network (CNN) landmark matching for VPR. First, based on the features extracted from existing CNN models, the regions with higher significance scores are selected as landmarks. Then, according to the coordinate positions of potential landmarks, landmark matching is improved by removing mismatched landmark pairs. Finally, considering the significance scores obtained in the first step, robust image retrieval is performed based on adaptive landmark matching, and it gives more weight to the landmark matching pairs with higher significance scores. To verify the efficiency and robustness of the proposed method, evaluations are conducted on standard benchmark datasets. The experimental results indicate that the proposed method reduces the feature representation space of place images by more than 75% with negligible loss in recognition precision. Also, it achieves a fast matching speed in similarity calculation, satisfying the real-time requirement.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.59 no.3
• /
• pp.261-263
• /
• 2023

Recently, universities of fisheries and institutions related to fisheries are actively carrying out a project to build new fisheries training ships. These new fisheries training ships are significantly larger in size and longer in length than the previous ships. In addition, these new ships basically have space that can accommodate more than 100 crew and passenger. On the other hand, they are excluded from IMO maneuverability evaluation since the size of these ships are still less than 100 m in length (LBP). These results have had an impact on the study of maneuverability of fishing vessels including the fisheries training ships. Against these backgrounds, the authors conducted a study to estimate the maneuvering characteristics of fisheries training ship Baek-Kyung according to depth in order to prepare a maneuvering characteristic index that enables the large fisheries training ships to navigate more safely using a modified empirical formula. It was confirmed that the maneuvering characteristics of Baek-Kyung changed significantly as the values of the hydrodynamic force coefficients changed as the water depth gradually decreased from around 1.5 (approx. 8 m in depth) of the ratio of the water depth to the ship draft. The results of this study will not only help navigators understand the maneuvering characteristics of Baek-Kyung, but also serve as an indicator when navigating in shallow water. In addition, the accumulation of these results will serve as a basis for future study on maneuverability of fishing vessel types.

• Journal of Korean Port Research
• /
• v.11 no.2
• /
• pp.305-320
• /
• 1997

The objective of this paper is to analysis & forecast on the change in spatial structures of southeast region by development of the Seoul-Pusan high-speed Rail. To measure the spatial structures, it was used the method of mean center and standard distance among of centrographic measures as analytical tools. The changes of spatial structures patten over time and space in the southeast region were surveyed using population and employment data of 57 zones. And also, to forecast the spatial structures of the southeast region after opening of the Seoul-Pusan high-speed rail, it was supposed three(3) scenarios which designed using influential area with centering around of the proposed high-speed rail stations. Therefore, the results of this research indicate as follows; 1) The spatial structures of population is showed a trend of continual concentration toward Ulsan city area, and also the spatial structures of employment is showed a trend of continual dispersion over time. 2) The forecast of three93) scenarios supposed after opening of the Seoul-Pusan high-speed rail in 2006 show a change of the spatial structures with both population concentration and employment dispersion. In the meantime, the rapid increase of population and wide dispersion of employment is reform with centering around HSR stations which builted in the southeast region after opening of high-speed rail. 3) It shall furnish valuable data to establish the development strategy of urban and local region, and also forecast the change of spatial structures about population and employment in influential area which passed on high-speed rail line & stations by method of mean center and standard distance among of centrographic measures as analytical tools.

• The Korean Journal of Air & Space Law and Policy
• /
• v.25 no.2
• /
• pp.113-137
• /
• 2010

The international community has done a lot of effort to improve the aviation safety. The new high technologies, systems and development of navigation equipments considerably improved the level of aviation safety. However, the aviation accident rate has been showing unchanged status without the decline since 1980. It means it is difficult to secure enough safety by the existing efforts to improve the aviation safety, eventually needs new methods for the accident prevention. With this in mind, the nations interest new methods that can consider a countermeasure by realizing potential risk factors before fatal accidents. In other words, that is to analyze and share the safety information collected from accidents by establishing aviation safety information system. To establish international aviation safety information system, each country's aviation accident incident reporting systems are need to be established. Also aviation safety data taxonomy is need to be standardized. Then, aviation users will communicate the information efficiently. This study investigates and considers each country's aviation accident incident database taxonomy for the analysis of the aviation data and the necessary prevention activity. This will contribute to a better international aviation safety and strengthen the country's aviation diplomacy.