• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.102-108
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• 2008

This paper describes a mapping and localization based on wave algorithm[11] and Kalman filter for effective SLAM. Each robot in a multi robot system has its own task such as building a map for its local position. By combining their data into a shared map, the robot scans actively seek to verify their relative locations. For simultaneous localization the algorithm which is well known as Kalman Filter (KF) is used. For modelling the robot position we wish to know three parameters (x, y coordinates and its orientation) which can be combined into a vector called a state variable vector. The Kalman Filter is a smart way to integrate measurement data into an estimate by recognizing that measurements are noisy and that sometimes they should ignored or have only a small effect on the state estimate. In addition to an estimate of the state variable vector, the algorithm provides an estimate of the state variable vector uncertainty i.e. how confident the estimate is, given the value for the amount of error in it.

• Knowledge Management Research
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• v.11 no.2
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• pp.75-93
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• 2010

Even though there have been many efforts on driver's route recommendation, driver still should get involved to choose the driving path in a manual manner. Uncertain traffic information provided to the driver delays his arrival time and hence may cause diminished economic values. One of the solutions of reducing the uncertainty is to provide various kinds of traffic information, rather than send real-time information. Therefore, as the wireless communication technology improves and at the same time volume of utilizable traffic contents increases in geometrical progression, selecting traffic information based on driver's context in a timely and individual manner will be needed. Hence, the purpose of this paper is to propose a methodology that efficiently sends the rich traffic contents to the personal in-vehicle navigation. To do so, driver preference is modeled and then the recommendation algorithm of traffic information contents was developed using the preference model. Secondly, ontology based traffic situation analyzation method is suggested to automatically inference the noticeable information from the traffic context on driver's route. To show the feasibility of the idea proposed in this paper, an open API service is implemented in consideration of ease of use.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.398-405
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• 2005

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Also, the control method is proposed to estimate position and direction between the walking human and the mobile robot, and the Kalman filter scheme is used for the estimation of the mobile robot localization. And its performance is verified by the computer simulation and the experiment.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.251-268
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• 2007

A Gaussian sum filter (GSF) is proposed in this paper on simultaneous localization and mapping (SLAM) for mobile robot navigation. In particular, the SLAM problem is tackled here for cases when only bearing measurements are available. Within the stochastic mapping framework using an extended Kalman filter (EKF), a Gaussian probability density function (pdf) is assumed to describe the range-and-bearing sensor noise. In the case of a bearing-only sensor, a sum of weighted Gaussians is used to represent the non-Gaussian robot-landmark range uncertainty, resulting in a bank of EKFs for estimation of the robot and landmark locations. In our approach, the Gaussian parameters are designed on the basis of minimizing the representation error. The computational complexity of the GSF is reduced by applying the sequential probability ratio test (SPRT) to remove under-performing EKFs. Extensive experimental results are included to demonstrate the effectiveness and efficiency of the proposed techniques.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.72-81
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• 2023

We introduce tightly-coupled GNSS-LiDAR-Inertial state estimator, which is capable of SLAM (Simultaneously Localization and Mapping) and autonomous driving. Long term drift is one of the main sources of estimation error, and some LiDAR SLAM framework utilize loop closure to overcome this error. However, when loop closing event happens, one's current state could change abruptly and pose some safety issues on drivers. Directly utilizing GNSS (Global Navigation Satellite System) positioning information could help alleviating this problem, but accurate information is not always available and inaccurate vertical positioning issues still exist. We thus propose our method which tightly couples raw GNSS measurements into LiDAR-Inertial SLAM framework which can handle satellite positioning information regardless of its uncertainty. Also, with NLOS (Non-light-of-sight) satellite signal handling, we can estimate our states more smoothly and accurately. With several autonomous driving tests on AGV (Autonomous Ground Vehicle), we verified that our method can be applied to real-world problem.

• Journal of Korean Port Research
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• v.12 no.1
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• pp.9-17
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• 1998

The evaluation structure of complex problems is composed of multi-attributes and hierarchy. A many studies were existed on this problems, but that based on the assumption that the evaluation elements were independent. The actual evaluation problems have the complexity, ambiguity and interlinkage among the elements. In this situation, the fuzzy evaluation process is very effective in settling the complex problems. For evaluation of large scale hierarchical MADM problem, the fuzzy evaluation algorithm is developed in this paper, and that is centering on the identification of fuzzy measures. In this study, we newly identified the weight and interaction among the evaluation attributes. The results of this study are as follows: we can identified the hierarchical structure of the evaluation problem which is composed of the evaluation structure, function and hierarchy; we improved the existed weighting method which could be accomplished by normalizing process, considering the uncertainty and new weight integrating method which come from Dempster-Shafer theory. And we take into account the interaction properties among more than 3 evaluation attributes, which can be compared with the existed studies in which only 2 evaluation attributes taked into account.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.3
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• pp.125-133
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• 2017

Time comparison is necessary for the verification and synchronization of the clock. Two-way satellite time and frequency (TWSTFT) is a method for time comparison over long distances. This method includes errors such as atmospheric effects, satellite motion, and environmental conditions. Ionospheric delay is one of the significant time comparison error in case of the carrier-phase TWSTFT (TWCP). Global Ionosphere Map (GIM) from Center for Orbit Determination in Europe (CODE) is used to compare with Bernese. Thin shell model of the ionosphere is used for the calculation of the Ionosphere Pierce Point (IPP) between stations and a GEO satellite. Korea Research Institute of Standards and Science (KRISS) and Koganei (KGNI) stations are used, and the analysis is conducted at 29 January 2017. Vertical Total Electron Content (VTEC) which is generated by Bernese at the latitude and longitude of the receiver by processing a Receiver Independent Exchange (RINEX) observation file that is generated from the receiver has demonstrated adequacy by showing similar variation trends with the CODE GIM. Bernese also has showed the capability to produce high resolution IONosphere map EXchange (IONEX) data compared to the CODE GIM. At each station IPP, VTEC difference in two stations showed absolute maximum 3.3 and 2.3 Total Electron Content Unit (TECU) in Bernese and GIM, respectively. The ionospheric delay of the TWCP has showed maximum 5.69 and 2.54 ps from Bernese and CODE GIM, respectively. Bernese could correct up to 6.29 ps in ionospheric delay rather than using CODE GIM. The peak-to-peak value of the ionospheric delay for TWCP in Bernese is about 10 ps, and this has to be eliminated to get high precision TWCP results. The $10^{-16}$ level uncertainty of atomic clock corresponds to 10 ps for 1 day averaging time, so time synchronization performance needs less than 10 ps. Current time synchronization of a satellite and ground station is about 2 ns level, but the smaller required performance, like less than 1 ns, the better. In this perspective, since the ionospheric delay could exceed over 100 ps in a long baseline different from this short baseline case, the elimination of the ionospheric delay is thought to be important for more high precision time synchronization of a satellite and ground station. This paper showed detailed method how to eliminate ionospheric delay for TWCP, and a specific case is applied by using this technique. Anyone could apply this method to establish high precision TWCP capability, and it is possible to use other software such as GIPSYOASIS and GPSTk. This TWCP could be applied in the high precision atomic clocks and used in the ground stations of the future domestic satellite navigation system.

• The Korean Journal of Air & Space Law and Policy
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• v.26 no.1
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• pp.241-269
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• 2011

Solar flare and storm may give an adverse effect upon electromagnetic environment around the Earth, so that various kinds of satellite cease to normally function. This kind of space storm disaster is characterized by the uncertainty about when and what size. Recently the UN has been paying attention to this plausible disaster. Particularly the COPUOS has taken the view that this disaster would threaten the sustainable space environment. The precautionary principle, rooted and excercised in the environment protection filed, has been adopted in the case of disaster with uncertainty. The reports and opinions given by the expert and representatives of the member States have stated that the precautionary principle should be adopted for the purpose of dealing with this disaster. On the other hand, it is advanced that the principle has been already included in the space law principle enshrined in the 1967 Space Treaty. The Treaty has adopted the freedom of navigation and use of the outer space for the interest of all States as the basic principles. Sustainable environment is necessary for implementing the principle. Therefore, the rules for the protection of sustainable space environment should be based upon the space law principle.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.462-469
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• 2023

In this study, we propose a method for evaluating the risk of collision between ships to support determination on the risk of collision in a situation in which ships encounter each other and to prevent collision accidents. Because several uncertainties are involved in the navigation of a ship, must be considered when evaluating the risk of collision. We apply the Dempster-Shafer theory to manage this uncertainty and evaluate the collision risk of each target vessel in real time. The distance at the closest point approach (DCPA), time to the closest point approach (TCPA), distance from another vessel, relative bearing, and velocity ratio are used as evaluation factors for ship collision risk. The basic probability assignments (BPAs) calculated by membership functions for each evaluation factor are fused through the combination rule of the Dempster-Shafer theory. As a result of the experiment using automatic identification system (AIS) data collected in situations where ships actually encounter each other, the suitability of evaluation was verified. By evaluating the risk of collision in real time in encounter situations between ships, collision accidents caused by human errora can be prevented. This is expected to be used for vessel traffic service systems and collision avoidance systems for autonomous ships.

• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.479-484
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• 2007

For calculation of wave field for design of coastal and port structures, generally the wind fields from inland observation record or the predicted waves from deep water wave transformation model are being used. However, for the first case, as we should revise the wave data adopting correcting parameters depending on the distance from the coast and location, it is difficult to extract water waves from wind field. Furthermore, for the second case, because of the calculation which executed under very large grid sizes in the wide domain, the simulation(wave transformation) implied uncertainty in the near shore area and shallow region. So it's difficult to obtain exact data from the simulation. Thus, in this study the calculation of wave field on shallow water is accomplished using the observed data of typhoon 'Maemi' in the Korea Eastern South sea. Moreover, for the accuracy of the calculated wave field, we compared and studied the observed data of wave height and direction on the vicinity of the Ulsan waters. It is proved that the results of this study is more accurate than the existing method with showing ${\pm}1.3%$ difference between observed and calculated wave height distribution in Ulsan waters