• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.4
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• pp.315-321
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• 2017

This paper is a study on the design and realization of Pedestrian navigation service system for the visually impaired. As it is an user interface considering visually impaired, voice recognition functioned smartphone was used as the input tool and the Osteoacusis headset, which can vocally guide directions while recognizing the surrounding environment sound, was used as the output tool. Unlike the pre-existing pedestrian navigation smartphone apps, the developed system guides walking direction by the scale of the left and right stereo sound of the headset wearing, and the voice guidance about the forked or curved path is given several meters before according to the speed of the user, and the user is immediately warned of walking opposite direction or proceeding off the path. The system can acquire stable and reliable directional information using the motion tracker with the dynamic heading accuracy of 1.5 degrees. In order to overcome GPS position error, we proposed a robust trajectory planning algorithm for position error. Experimental results for the developed system show that the average directional angle error is 6.82 degrees (standard deviation: 5.98) in the experimental path, which can be stated that it stably navigated the user relatively.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.9
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• pp.281-290
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• 2020

The Vision-and-Language Navigation(VLN) task is a complex intelligence problem that requires both visual and language comprehension skills. In this paper, we propose a new learning model for visual-language navigation agents. The model adopts a hybrid learning that combines imitation learning based on demo data and reinforcement learning based on action reward. Therefore, this model can meet both problems of imitation learning that can be biased to the demo data and reinforcement learning with relatively low data efficiency. In addition, the proposed model uses a novel path-based reward function designed to solve the problem of existing goal-based reward functions. In this paper, we demonstrate the high performance of the proposed model through various experiments using both Matterport3D simulation environment and R2R benchmark dataset.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3270-3294
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• 2020

Some things come easily to humans, one of them is the ability to navigate around. This capability of navigation suffers significantly in case of partial or complete blindness, restricting life activity. Advances in the technological landscape have given way to new solutions aiding navigation for the visually impaired. In this paper, we analyze the existing works and identify the challenges of path selection, context awareness, obstacle detection/identification and integration of visual and nonvisual information associated with real-time assisted mobility. In the process, we explore machine learning approaches for robotic path planning, multi constrained optimal path computation and sensor based wearable assistive devices for the visually impaired. It is observed that the solution to problem is complex and computationally intensive and significant effort is required towards the development of richer and comfortable paths for safe and smooth navigation of visually impaired people. We cannot overlook to explore more effective strategies of acquiring surrounding information towards autonomous mobility.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.06a
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• pp.172-174
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• 2012

The maritime traffic system research has been studied for the safety and efficiency of the Marine Navigation. In order to evaluate the maritime traffic system, the vessel traffic observation is playing important roll. Recently, the way of collecting the vessel traffic information has been become fixed by using the radar, the AIS and the visual observations. However, it is still difficult to get the information about ships without the AIS. In this paper, the past vessel traffic observation results are shown. From those data and introducing the way of Japanese traffic survey, the recent matters of the vessel traffic observation are discussed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.79-80
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• 2007

An expert system of collision avoidance developed by CLIPS and Visual C++ is continuously introduced in this paper. Further, a simulation function of collision avoidance is added to the expert system, the function can simulate the avoidance actions of own ship and a specific target of a period of future time. This function can help navigators to estimate collision risk and make proper collision avoidance actions in dangerous situations for navigational safety of ships. Furthermore, navigational rules can also be evaluated during the process of simulation.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.61-63
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• 2005

Retreiving indoor scene reference image from database using visual information is important issue in Robot Navigation. Scene matching problem in navigation robot is not easy because input image that is taken in navigation process is affinly distorted. We represent probabilistic framework for the feature matching between features in input image and features in database reference images to guarantee robust scene matching efficiency. By reconstructing probabilistic scene matching framework we get a higher precision than the existing feaure-feature matching scheme. To construct probabilistic framework we represent each image as Gaussian Mixture Model using Expectation Maximization algorithm using SIFT(Scale Invariant Feature Transform).

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.222-225
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• 1989

A method is proposed to design a mobile tele-existence system, which can be remotely driven with the auditory and visual sensation of presence. The system consists of mobile robot with camera and two microphones. The effectiveness of the proposed system was evaluated by navigation experiments of the tele-robot through an obstructed space.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2003.05a
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• pp.70-77
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• 2003

가상환경에서의 실재감을 증대시키는 방법 중에 하나는 상호작용을 이용하는 방법이다. 즉, 사용자가 가상환경에 변화를 줄 수 있게 하여, 사용자와 가상환경 사이의 결속감을 통해, 사용자가 가상환경 속에 있는 듯한 느낌을 주는 것이다. 그러나, Architectural Walkthrough 혹은 Navigation 시스템은 기능적으로 가상객체와에 affordance 와 그 밖의 interactivity cue를 적용하여 사용자로 하여금 시각적으로만 상호작용감을 유발하게 하여, 사용자의 실재감을 높이기 위한 방법에 대한 것이다. 두 개의 가상환경에 대하여 아무런 visual cue가 없는 경우, 텍스트를 이용한 직접 표현 방법, 객체가 simulation 된 trace 그리고 affordance cue 등 총 4가지 방법들, 즉 총 8가지 실험 조합에서 사용자가 느끼는 상호작용성과 실재감을 측정하였는데 interactivity유도를 위한 간접적인 visual cue가 쓰였을 경우 통계적으로 유의하게 상호작용성 및 실재감이 증대하는 결과를 보여주었다. 이는 적은 모델링만의 노력으로, 실제 인터액션에 대한 구현 없이 가상환경에서 어느 정도의 실재감을 높일 수 있는 방법을 제시하고 있다.

• Journal of Advanced Navigation Technology
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• v.11 no.1
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• pp.105-111
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• 2007

This paper is concerned with fuzzy inference-based optimal sub-bands decision scheme which is to be embedded the watermark. It concentrated not only on design of fuzzy inference algorithm but also on human visual parameters (HVP), such as contrast sensitivity, texture degree. In the first, such human visual parameters as contrast sensitivity, texture degree as well as statistical characteristics are involved to select the optimal coefficients region. Secondly, fuzzy if - then rule which can be able to adapt the wide variety of environments is developed. The performance of proposed approach is evaluated with respect to the imperceptibility and correctness of watermark. According to some experimental results, contrast sensitivity function is superior in smooth image. On the other hand, statistical characteristics provide good results in rough images.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.434-443
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• 2007

Presently, the exploration of an unknown environment is an important task for thee new generation of mobile service robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems. This paper presents a technique for localization of a mobile robot using fusion data of multi-ultrasonic sensors and vision system. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, comers and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD(Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a vision-based environment recognition, phisically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.