• Journal of Positioning, Navigation, and Timing
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• 제5권3호
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• pp.119-129
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• 2016

This paper presents an integrated navigation system for accurate navigation solution-based safety and convenience services in the vehicular augmented reality (AR)-head up display (HUD) system. For lane-level guidance service, especially, an accurate navigation system is essential. To achieve this, an inertial navigation system (INS)/global positioning system (GPS)/vision/digital map (IGVM) integrated navigation system has been developing. In this paper, the concept of the integrated navigation system is introduced and is implemented based on a multi-model switching filter and vehicle status decided by using the GPS data and inertial measurement unit (IMU) measurements. The performance of the implemented navigation system is verified experimentally.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권10호
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• pp.703-713
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• 2004

This paper presents the new obstacle avoidance method that is composed of vision and sonar sensors, also a navigation algorithm is proposed. Sonar sensors provide poor information because the angular resolution of each sonar sensor is not exact. So they are not suitable to detect relative direction of obstacles. In addition, it is not easy to detect the obstacle by vision sensors because of an image disturbance. In This paper, the new obstacle direction measurement method that is composed of sonar sensors for exact distance information and vision sensors for abundance information. The modified splitting/merging algorithm is proposed, and it is robuster for an image disturbance than the edge detecting algorithm, and it is efficient for grouping of the obstacle. In order to verify our proposed algorithm, we compare the proposed algorithm with the edge detecting algorithm via experiments. The direction of obstacle and the relative distance are used for the inputs of the fuzzy controller. We design the angular velocity controllers for obstacle avoidance and for navigation to center in corridor, respectively. In order to verify stability and effectiveness of our proposed method, it is apply to a vision and sonar based mobile robot navigation system.

• 한국항공우주학회지
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• 제47권4호
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• pp.274-282
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• 2019

무인항공기의 영상 기반 항법은 널리 사용되는 GPS/INS 통합 항법 시스템의 취약점을 보강할 수 있는 중요한 기술로 이에 대한 연구가 활발히 이루어지고 있다. 하지만 일반적인 영상 대조 기법은 실제 항공기 비행 상황들을 적절하게 고려하기 힘들다는 단점이 있다. 따라서 본 논문에서는 영상기반 항법을 위한 가우시안 혼합 모델 기반의 파티클 필터를 제안한다. 제안한 파티클 필터는 영상과 데이터베이스를 가우시안 혼합 모델로 가정하여 둘 간의 유사도를 이용하여 항체의 위치를 추정한다. 또한 몬테카를로 시뮬레이션을 통해 위치 추정 성능을 확인한다.

• 대한임베디드공학회논문지
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• 제3권2호
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• pp.57-65
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• 2008

Recently many researches on intelligent robots have been studied. An intelligent robot is capable of recognizing environments or objects to autonomously perform specific tasks using sensor readings. One of fundamental problems in vision-based robot applications is to recognize where it is and to decide safe path to perform autonomous navigation. However, previous approaches only consider well-organized environments that there is no moving object and environment changes. In this paper, we introduce a novel navigation strategy to handle occlusions caused by moving objects using various computer vision techniques. Experimental results demonstrate the capability to overcome such difficulties for autonomous navigation.

• 로봇학회논문지
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• 제11권4호
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• pp.226-234
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• 2016

In this study, a model-referenced underwater navigation algorithm is proposed for high-precise underwater navigation using monocular vision near underwater structures. The main idea of this navigation algorithm is that a 3D model-based pose estimation is combined with the inertial navigation using an extended Kalman filter (EKF). The spatial information obtained from the navigation algorithm is utilized for enabling the underwater robot to navigate near underwater structures whose geometric models are known a priori. For investigating the performance of the proposed approach the model-referenced navigation algorithm was applied to an underwater robot and a set of experiments was carried out in a water tank.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2012년도 추계학술대회 논문집
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• pp.641-642
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• 2012

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.423-424
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• 2013

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1097-1107
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• 2001

In this paper, the wall following navigation algorithm of the mobile robot using a mono vision system is described. The key points of the mobile robot navigation system are effective acquisition of the environmental information and fast recognition of the robot position. Also, from this information, the mobile robot should be appropriately controlled to follow a desired path. For the recognition of the relative position and orientation of the robot to the wall, the features of the corridor structure are extracted using the mono vision system, then the relative position, the offset distance and steering angle of the robot from the wall, is derived for a simple corridor geometry. For the alleviation of the computation burden of the image processing, the Kalman filter is used to reduce search region in the image space for line detection. Next, the robot is controlled by this information to follow the desired path. The wall following control scheme by the PD control scheme is composed of two control parts, the approaching control and the orientation control, and each control is performed by steering and forward-driving motion of the robot. To verify the effectiveness of the proposed algorithm, the real time navigation experiments are performed. Through the result of the experiments, the effectiveness and flexibility of the suggested algorithm are verified in comparison with a pure encoder-guided mobile robot navigation system.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.377-382
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• 2006

Precision approach and landing of aircraft in a remote landing zone autonomously present several challenges. Firstly, the exact location, orientation and elevation of the landing zone are not always known; secondly, the accuracy of the navigation solution is not always sufficient for this type of precision maneuver if there is no DGPS availability within close proximity. This paper explores an alternative approach for estimating the navigation parameters of the aircraft to the landing area using only time-differenced GPS carrier phase measurement and range measurements from a vision system. Distinct ground landmarks are marked before the landing zone. The positions of these landmarks are extracted from the vision system then the ranges relative to these locations are used as measurements for the extended Kalman filter (EKF) in addition to the precise time-differenced GPS carrier phase measurements. The performance of this navigation algorithm is demonstrated using simulation.

• 한국군사과학기술학회지
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• 제14권2호
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• pp.271-280
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• 2011

This paper presents a navigation system based on the tactical communication and vision system in outdoor environments which is applied to unmanned robot for perimeter surveillance operations. GPS errors of robot are compensated by the reference station of C2(command and control) vehicle and WiBro(Wireless Broadband) is used for the communication between two systems. In the outdoor environments, GPS signals can be easily blocked due to trees and buildings. In this environments, however, vision system is very efficient because there are many features. With the feature MAP around the operation environments, the robot can estimate the position by the image matching and pose estimation. In the navigation system, thus, operation modes is switched by navigation manager according to some environment conditions. The experimental results show that the unmanned robot can estimate the position very accurately in outdoor environment.