• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1738-1745
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• 2016

In this paper, we present localization and autonomous navigation method using GPU(Graphics Processing Unit)-based SIFT(Scale-Invariant Feature Transform) algorithm and virtual force method for mobile robots. To do this, at first, we propose the localization method to recognize the landmark using the GPU-based SIFT algorithm and to update the position using extended Kalman filter. And then, we propose the A-star algorithm for path planning and the virtual force method for autonomous navigation of the mobile robot. Finally, we demonstrate the effectiveness and applicability of the proposed method through some experiments using the mobile robot with OPRoS(Open Platform for Robotic Services).

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1044-1049
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• 2015

This paper proposes an autonomous navigation system of mobile robots for indoor corridor environment. The system uses a laser scanner but does not use reflectors. The laser scanner measures the distance between robot and structures such as wall, pillar, and fixtures. Adaptive breakpoint detector and modified IEPF (iterative endpoint fit) are developed to find mark points from the distance data. The robot path for corridor is then generated using the angle histogram of the mark points. The experimental results are finally presented to show the effectiveness of the proposed method.

• Journal of Advanced Navigation Technology
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• v.23 no.4
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• pp.289-295
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• 2019

Maritime back-up navigation system in port approach requires a horizontal accuracy of 10 meters in IALA (International Association of Lighthouse Authorities) recommendations. eLoran which is a best back-up navigation system that satisfies accuracy requirement has poor navigation performance depending signal environments. Especially, noise caused by multipath and electronic devices around eLoran antenna affects navigation performance. In this paper, Ship based Navigation Back-up system using UAV on Interference is designed to satisfy horizontal accuracy requirement. To improve the eLoran signal environment, UAVs are equipped with camera, IMU sensor and eLoran antenna and receivers. This proposed system is designed to receive eLoran signal through UAV-based receiver and control UAV's position and attitude within Landmark around area. The ship-based positioning using eLoran signal, vision and attitude information received from UAV satisfy resilient and robust navigation requirements.

• Journal of Korean Neurosurgical Society
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• v.53 no.3
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• pp.150-154
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• 2013

Objective : To evaluate the effect of electromagnetic (EM) navigation system on ventriculoperitoneal (VP) shunt failure rate through comparing the result of standard shunt placement. Methods : All patients undergoing VP shunt from October 2007 to September 2010 were included in this retrospective study. The first group received shunt surgery using EM navigation. The second group had catheters inserted using manual method with anatomical landmark. The relationship between proximal catheter position and shunt revision rate was evaluated using postoperative computed tomography by a 3-point scale. 1) Grade I; optimal position free-floating in cerebrospinal fluid, 2) Grade II; touching choroid or ventricular wall, 3) Grade III; tip within parenchyma. Results : A total of 72 patients were participated, 27 with EM navigated shunts and 45 with standard shunts. Grade I was found in 25 patients from group 1 and 32 patients from group 2. Only 2 patients without use of navigation belonged to grade III. Proximal obstruction took place 7% in grade I, 15% in grade II and 100% in grade III. Shunt revision occurred in 11% of group 1 and 31% of group 2. Compared in terms of proximal catheter position, there was growing trend of revision rate according to increase of grade on each group. Although infection rate was similar between both groups, the result had no statistical meaning (p=0.905, chi-square test). Conclusion : The use of EM navigation in routine shunt surgery can eliminate poor shunt placement resulting in a dramatic reduction in failure rates.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.529-539
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• 1999

This paper suggests a new image analysis method and indoor navigation control algorithm of mobile robots using a mono vision system. In order to reduce the positional uncertainty which is generated as the robot travels around the workspace, we propose a new visual landmark recognition algorithm with 2-D graph world model which describes the workspace as only a rough plane figure. The suggested algorithm is implemented to our mobile robot and experimented in a real corridor using extended Kalman filter. The validity and performance of the proposed algorithm was verified by showing that the trajectory deviation error was maintained under 0.075m and the position estimation error was sustained under 0.05m in the resultant trajectory of the navigation.

• Journal of Navigation and Port Research
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• v.35 no.4
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• pp.317-321
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• 2011

In this paper, a foggy-degraded image restoration technique with a physics-based degradation model is proposed for the measurement system. When the degradation model is used for the image restoration, its parameters and a distance from the spreader to the camera have to be previously known. In the proposed image restoration technique, the parameters are estimated from variances and averages of intensities on two foggy-degraded landmark images taken at different distances. Foggy-degraded images can be restored with the estimated parameters and the distance measured by the measurement system. On the basis of the experimental results, the performance of the proposed foggy-degraded image restoration technique was verified.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.11a
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• pp.109-117
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• 2000

This study aims at advancing waterfront of Pusan Port and attempting to establish an identity through studying characteristics of place in Pusan Port. The place is consisted of two elements ; orientation and identity, which is expressed clearly the environmental totality including the character and space. The urban waterfront is also one of the place pattern, and that is consist of land area, water area, and transit zone combining two areas. Although there are a lot of primary factors to be able to make the most of the character and identity in Pusan port, badly planned development prevents the plan promoting the sense of place in urban waterfront. The point in the waterfront development plan of Pusan Port is how to secure aminities based on Identity and Orientation; node, landmark, edge, path, district. The result of this study is for planners to develop more and systematic approaches which could utilize waterfront.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.108-118
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• 2017

This paper presents experimental results of realtime sonar-based SLAM (simultaneous localization and mapping) using probability-based landmark-recognition. The sonar-based SLAM is used for navigation of underwater robot. Inertial sensor as IMU (Inertial Measurement Unit) and DVL (Doppler Velocity Log) and external information from sonar image processing are fused by Extended Kalman Filter (EKF) technique to get the navigation information. The vehicle location is estimated by inertial sensor data, and it is corrected by sonar data which provides relative position between the vehicle and the landmark on the bottom of the basin. For the verification of the proposed method, the experiments were performed in a basin environment using an underwater robot, yShark.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.667-675
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• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.389-394
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• 2006

Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localization technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.