• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1044-1050
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• 2014

Robots used for pipe inspection have been studied for a long time and many mobile mechanisms have been proposed to achieve inspection tasks within pipelines. Localization is an important factor for an inpipe robot to perform successful autonomous operation. However, sensors such as GPS and beacons cannot be used because of the unique characteristics of inpipe conditions. In this paper, an inpipe localization algorithm based on elbow detection is presented. By processing the projected marker images of laser pointers and the attitude and heading data from an IMU, the odometer module of the robot determines whether the robot is within a straight pipe or an elbow and minimizes the integration error in the orientation. In addition, an off-line positioning algorithm has been performed with forward and backward estimation and Procrustes analysis. The experimental environment has consisted of several straight pipes and elbows, and a map of the pipeline has been constructed as the result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3373-3389
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• 2022

Exploration of mobile robot without prior data about environments is a fundamental problem during the SLAM processes. In this work, we propose improved version of previous Rmap algorithm by modifying its Exploration submodule. Despite the previous Rmap's performance which significantly reduces the overhead of the grid map, its exploration module costs a lot because of its rectangle following algorithm. To prevent that, we propose a new Rmap+ algorithm for autonomous path planning of mobile robot to explore an unknown environment. The algorithm bases on paired frontiers. To navigate and extend an exploration area of mobile robot, the Rmap+ utilizes the inner and outer frontiers. In each exploration round, the mobile robot using the sensor range determines the frontiers. Then robot periodically changes the range of sensor and generates inner pairs of frontiers. After calculating the length of each frontiers' and its corresponding pairs, the Rmap+ selects the goal point to navigate the robot. The experimental results represent efficiency and applicability on exploration time and distance, i.e., to complete the whole exploration, the path distance decreased from 15% to 69%, as well as the robot decreased the time consumption from 12% to 86% than previous algorithms.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.279-280
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• 2022

도로를 주행 중인 운전자들은 비상용 차량이 접근할 때 경광등 혹은 백미러를 통해 확인하고, 도로의 상황을 파악한 후에서야 길을 양보한다. 그러나 비상 차량이 접근하는 걸 뒤늦게 인지하거나, 도로의 상황이 복잡하여 차선을 변경하다 접촉사고가 발생할 수도 있고, 또한 진행할 수 있는 도로를 미리 확보하지 못하여 비상 차량이 정해진 시간 내에 도착하지 못하는 경우가 자주 발생하고 있다. 이러한 일을 개선하기 위해서 본 논문에서는 안드로이드, GPS 기술을 이용한 앱을 통해 비상 차량이 일반 차량에 일정 거리 이내에 접근할 경우에 미리 알람을 보내고 이를 사전에 방지, 및 예방할 수 있는 앱을 개발한다. 안드로이드 스튜디오를 사용하였고, Firebase를 이용해 DB및 서버를 구축하였다.

• Ocean Systems Engineering
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• v.14 no.2
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• pp.101-114
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• 2024

Seafloor sediment mapping is an essential research topic in shallow coastal waters, especially in port development, benthic habitat mapping, and underwater communications. The seafloor sediments can be interpreted by collecting sediment samples directly in the field using a grab sampler or corer. Another method is optical, especially using underwater cameras and videos. Both methods each have weaknesses in terms of area coverage (mechanic) and accurate positioning (optic). The latest technology used to overcome it is the acoustic method (echosounder) with Global Navigation Satellite System (GNSS) Real Time Kinematic (RTK) positioning. Therefore, in this study will propose the classification of seafloor sediments in coastal waters using acoustic method that is Multibeam Echosounder (MBES) multi-frequency with five frequency (200 kHz, 250 kHz, 300 kHz, 350 kHz, and 400 kHz). In this study, the deep neural network (DNN) used the bathymetric multi frequency, bathymetric difference inters frequencies, and bathymetric features from 5 (five) frequencies as input layer and 4 (four) sediment types in 74 (seventy-four) sample sediment as output layer to make a seafloor sediment map. Results of sediment mapping using the DNN method show an overall accuracy of 71.6% (significant) and a kappa coefficient of 0.59 (moderate). The distribution of seafloor sediment in the study area is mainly silt (41.6%), followed by clayey sand (36.6%), sandy silt (14.2%), and silty sand (7.5%).

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.10
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• pp.530-540
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• 2005

Virtual colonoscopy is an easy and fast method to reconstruct the shape of colon and diagnose tumors inside the colon based on computed tomography images. This is a non-invasive method, which resolves weak points of previous invasive methods. The path for virtual colonoscopy should be generated rapidly and accurately for clinical examination. However, previous methods are computationally expensive because the data structure such as distance map should be constructed in the preprocessing and positions of all the points of the path needs to be calculated. In this paper, we propose the automatic path generation method based on visibility to decrease path generation time. The proposed method does not require preprocessing and generates small number of control points representing the Path instead of all points to generate the path rapidly. Also, our method generates the path based on visibility so that a virtual camera moves smoothly and a comfortable and accurate path is calculated for virtual navigation. Also, our method can be used for general virtual navigation of various kinds of pipes.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.115-125
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• 2017

In current, as the release of national base map with an equivalent scale and accuracy for the whole territory areas in South Korea, rapid spatial information industry such as national land development, GIS, and car navigation are used in a variety of spatial information industry as decision making method, and a lot of research and policies are proposed for the wide expansion of spatial information industry. For this, as of 2013, it contributes to the latest trend of spatial information field in order to solve the problems for the latest trend of spatial information, replacing modification of base maps as dividing the whole territory to zone with policy transformation by ordinary modifications. Therefore, this paper evaluates the possibility of modification and renewal of national base maps(scale: 1:5,000) using drones which currently get the limelight from a variety of research fields and industries. In particular, as a result of overlapping orthophoto, 3D point clouds extracted from images acquired by low-cost drones, and digital maps which are applied for the tasks of modification and renewal, it presents 0.2m precision and 0.1m accuracy. This means that drone-based photorgammetry technique can be fully utilized in the tasks of digital map modification and renewal because it conforms the error range of work regulation in making the national base maps(scale 1: 5000).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.483-491
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• 2013

By a development of car navigation systems and mobile or positioning technology, it increases interest in location based services, especially pedestrian navigation systems. Updating of digital maps is important because digital maps are mass data and required to short updating cycle. In this paper, we proposed change detection for different network data-sets based on areal feature matching. Prior to change detection, we defined type of updating between different network data-sets. Next, we transformed road lines into areal features(block) that are surrounded by them and calculated a shape similarity between blocks in different data-sets. Blocks that a shape similarity is more than 0.6 are selected candidate block pairs. Secondly, we detected changed-block pairs by bipartite graph clustering or properties of a concave polygon according to types of updating, and calculated Fr$\acute{e}$chet distance between segments within the block or forming it. At this time, road segments of KAIS map that Fr$\acute{e}$chet distance is more than 50 are extracted as updating road features. As a result of accuracy evaluation, a value of detection rate appears high at 0.965. We could thus identify that a proposed method is able to apply to change detection between different network data-sets.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.591-598
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• 2020

The all revision of the Road Name Address Act, which contains the contents to be used by expanding the road name address as a means of indicationg the location, has been resloved by the National Assembly. Addresses will be assigned to large-sized facilities (3D mixed-use complex spaces). Here, the 3D (Three-dimensional) address is assigned an indoor path section in the inner passage, dividing the section at intervals. The 3D address will be built on the address information map. For 3D address, data should be built and managed for a 3D complex space(indoor space). Therefore, in this study, the object of the 3D address is defined based on the address conceptual model defined in the international standard, and the 3D address data model is proposed based on IndoorGML. To this, it is proposed as a method of mapping the Core and Navigation module of IndoorGML so that the entity of the 3D address can be expressed in IndoorGML. This study has a limitation in designing a 3D address data model only, but it is meaningful that it suggested a standard for constructing 3D address data in the future.

• Journal of Cadastre & Land InformatiX
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• v.46 no.1
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• pp.133-148
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• 2016

Voices demanding a revision of the aviation law on the operating drones are continuously rising high with the increase of their applicability in various industry fields. According to the current regulations, drones are permitted to fly under very strict conditions, which include limited places and the line-of-sight visibility from pilots. Because of the strict regulations, it is almost impossible for drones to be used in many industries such as parcel delivery services. To improve the business value of drones, we have to improve the accuracy of drones' positions and provide the proper protection levels in order to detect and avoid any risks including the collisions with the other drones. SBAS(Satellite Based Augmentation System) can support the aviation requirements with the accuracy and integrity so as to reduce the position errors and to calculate the protection levels of drones. In this paper, we assign the flight heights of drones according to the decision heights as per LAAS(Local Area Augmentation System) landing categories and conduct a simulation to predict the SBAS available time of the day.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.381-390
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• 2010

This paper describes a procedure of the map-based localization for mobile robots by using a sensor fusion technique in structured environments. A combination of various sensors with different characteristics and limited sensibility has advantages in view of complementariness and cooperation to obtain better information on the environment. In this paper, for robust self-localization of a mobile robot with a monocular camera and a laser structured light sensor, environment information acquired from two sensors is combined and fused by a Bayesian sensor fusion technique based on the probabilistic reliability function of each sensor predefined through experiments. For the self-localization using the monocular vision, the robot utilizes image features consisting of vertical edge lines from input camera images, and they are used as natural landmark points in self-localization process. However, in case of using the laser structured light sensor, it utilizes geometrical features composed of corners and planes as natural landmark shapes during this process, which are extracted from range data at a constant height from the navigation floor. Although only each feature group of them is sometimes useful to localize mobile robots, all features from the two sensors are simultaneously used and fused in term of information for reliable localization under various environment conditions. To verify the advantage of using multi-sensor fusion, a series of experiments are performed, and experimental results are discussed in detail.