• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.378-387
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• 2007

In this paper, Authors develop and verify the algorithm for enhancing the performance of Unmanned vehicle's Autonomous navigation, and also propose the method of establishing much more precise Navigation locus. Unmanned vehicle has a destination, however orientation is not notified, which make it find the future orientation itself. Extended Kalman Filter make it access to the desirable direction, which coupled with INS and GPS is proposed in this paper. Sliding mode control could overcome the side slip and lateral minor movement of the vehicle. The test result would shows the effectiveness of Extended kalman filter and Slide mode control for the navigation.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.755-760
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• 2011

This paper presents a method for improving the positioning accuracy of the laser navigation. As a wireless navigation system, the laser navigation which is more flexible than a wired guidance system is used for the localization and control of an AGV(automatic guided vehicle). However, the laser navigation causes the large positioning error while the AGV turns or moves fast. To solve the problem, we propose the method for improving the positioning accuracy of the laser navigation using particle filter which has robust and reliable performance in non-linear/non-gaussian systems. For the experiment, we use the actual fork-type AGV. The AGV has a gyro, two encoders and a laser navigation. To verify the performance, the proposed method is compared with the laser navigation which is a product. In the experimental result, we verified that the proposed method could improve the positioning accuracy by approximately 66.5%.

• Journal of Advanced Navigation Technology
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• v.23 no.4
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• pp.296-301
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• 2019

Artificial intelligence is closely linked to our real lives, leading innovation in various fields. Especially, as a means of transportation possessing artificial intelligence, autonomous unmanned vehicles are actively researched and are expected to be put into practical use soon. Autonomous cars and autonomous unmanned aerial vehicles are required to equip accurate navigation system so that they can find out their present position and move to their destination. At present, the navigation of transportation that we operate is mostly dependent on GPS. However, GPS is vulnerable to external intereference. In fact, since 2010, North Korea has jammed GPS several times, causing serious disruptions to mobile communications and aircraft operations. Therefore, in order to ensure safety in the operation of the autonomous unmanned vehicles and to prevent serious accidents caused by the intereference, rapid situation judgment and countermeasure are required. In this paper, based on big data and machine learning technology, we propose a countermeasure system for GPS interference that supports decision making by applying John Boyd's OODA loop cycle (detection - direction setting - determination - action).

• Journal of Ocean Engineering and Technology
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• v.22 no.4
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• pp.106-113
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• 2008

This paper presents an underwater navigation system based on range measurements from a known reference station fixed on the sea bottom or floated at surface with a buoy, for which the system is extended to 3-dimensional coordinates. We formulated a state equation in polar coordinates and constituted an extended Kalman filter for discrete-time implementation of the navigation algorithm. The autonomous underwater vehicle, lSiMl, cruising with a constant speed can estimate its trajectory using just range measurements and additional depth, heading and pitch sensors. Simulation studies were performed to evaluate the underwater navigation of the maneuvering AUV with range measurements. We modulated the sample rate of range measurements to evaluate the effect of the update rate, and changed the initial position error of the AUV to check the robustness to estimation errors. Simulation results illustrates that the extended navigation system provides convergence of the state estimates. The navigation system was conditionally stable when it had initial position errors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1343-1351
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• 2014

Recent technological advances in wireless networks and microelectromechanical systems (MEMS) have led to the development of different types of mini-UAVs and their utilizations in various ways. This study endeavors to develop a low-cost mini-UAV with autonomous flight capability, in order to obtain geospatial information of a small or medium-sized area, and also assess its flight stability by comparing the predetermined flight paths against the actual flight paths. Based on a post-development flight test, stable flight has been proven achievable as follows: the maximum endurance speed is 1 hour, the flying distance is 50km, the horizontal accuracy of flight paths is about ${\pm}6{\sim}8m$, and the altitude accuracy is about ${\pm}8m$. Therefore, it is deemed that high-resolution images which can be utilized for geospatial information are obtainable. This indicates that a UAV flying at an altitude of 200m can acquire images across a $2km{\times}3km$ area on the ground within 25 minutes, which validates its high usability for obtaining high-solution images at low altitudes in the future.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2218-2220
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• 2004

조종사 없이 사전에 입력된 프로그램 또는 인공지능에 의해 기체 스스로 판단하여 자율비행하는 비행체를 무인 항공기라 한다.[6] 이러한 비행을 위해서는 기체의 위치, 자세, 속도 등의 정보가 필요하다. 본 논문에서는 3축 가속도센서 1개 및 1축 자이로센서 3개를 서로 수직으로 구성하는 관성항법 시스템에 자기콤파스, 고도센서, GPS등의 비관성센서를 추가로 구성하여 시스템을 설계하였으며 칼만필터를 이용하여 시스템의 오차를 추정하고 이를 되먹임 시킴으로써 오차를 정정한다.

• Journal of Advanced Navigation Technology
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• v.11 no.2
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• pp.146-153
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• 2007

Autonomous unmanned vehicle is able to find the path and the way point by itself. For the more precise navigation performance, Extended kalman filter, which is integrated with inertial navigation system and global positioning system is proposed in this paper. Extended kalman filter's performance is evaluated by the simulation and applied to the unmanned vehicle. The test result shows the effectiveness of extended kalman filter for the navigation.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.101-108
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• 1998

This paper concerns the navigation algorithm of motion reference unit (MRU) for autonomous underwater vehicle (AUV) We apply the strapdown navigation system using middle level inertial sensors. But, because the MRU consists of inertial sensors, the values of AUV motion calculated by navigation computer are increased by drift property of inertial sensors. Therefore, we propose the attitude algorithm using switching method according to the motion of AUV From this algorithm, the drift terms are eliminated effectively for roll and pitch. But, another device is required for yaw angle.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.141-148
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• 2003

This paper presents a rotating ann test for assessment of an underwater hybrid navigation system for a semi-autonomous underwater vehicle. The navigation system consists of an inertial measurement unit (IMU), an ultra-short baseline (USBL) acoustic navigation sensor and a doppler velocity log (DVL) accompanying a magnetic compass. The errors of inertial measurement units increase with time due to the bias errors of gyros and accelerometers. A navigational system model is derived to include the error model of the USBL acoustic navigation sensor and the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 25 in the order. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors and correct the state equation when the measurements are available. The rotating ann tests are conducted in the Ocean Engineering Basin of KRISO, KORDI to generate circular motion in laboratory, where the USBL system was absent in the basin. The hybrid underwater navigation system shows good tracking performance against the circular planar motion. Additionally this paper checked the effects of the sampling ratio of the navigation system and the possibility of the dead reckoning with the DVL and the magnetic compass to estimate the position of the vehicle.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.82-83
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• 2022

국제해상충돌예방규칙(COLREGs)에 관한 협약은 해상에서 발생하는 충돌사고를 방지하기 위한 규칙으로 구성되어 있으며, Seaman(선원)의 Qualitative Rule(질적 규칙)과 Ordinary practice(통상적인 관행)에 기초하고 있다. MASS의 출현으로 인하여 질적 규칙과 관행으로 인하여 COLREG를 기반으로 한 항법 해석의 기준의 다름이 발생하였고, 기준의 차이로 인해 충돌 상황에 대한 항법 해석의 모호성문제가 발생하고 있다. 따라서 본 연구는 COLREG의 항법 해석의 모호성을 규명하여 유인과 무인 사이의 충돌회피 상황을 명확히 하는 것을 목적으로 한다. COLREG를 기반으로 한 충돌 상황의 모호성을 식별하기 위해 실제 항해사를 대상으로 충돌 회피 상황에 대한 인식을 조사하고, 정면 및 횡단, 횡단 및 추월 상황을 기반으로 조사 결과를 분석하였다. 분석 결과, 응답자들은 008°에서 마주치는 선박에 대해서 정면 또는 횡단 상황 항법 규칙을 적용해야 하는지, 160°에서 다가오는 선박에 대해서 추월 또는 횡단 상황을 적용해야 하는지에 대해 확신하지 못하는 것으로 나타났다. 이러한 결과는 이러한 모호성의 증가와 함께 충돌회피상황의 수동적 행동보다 능동적인 행동을 취함으로써 선원에 의한 충돌위험을 회피하려는 경향이 더 강해짐을 나타낸다.