• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2421-2423
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• 2002

A global ultrasonic sensor system for self-localization of an indoor mobile robot is proposed in this paper. By the global ultrasonic sensor system, it is meant several ultrasonic transmitters fixed at some positions in the world coordinate and the receiver in the moving coordinate of a mobile robot. In order to achieve the synchronization between an ultrasonic transmitter and receiver and to avoid the crosstalk among the ultrasonic transmitters, simple radio frequency transmitters and receivers are adopted. Experiments are carried out to verify the effectiveness of the proposed ultrasonic sensor system.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.3
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• pp.161-167
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• 2018

The improvement of the social environment and the rapid development of medicine are making possible the age of 100. So a great number of countries including Korea are rapidly becoming the aged society or the super aged society. The elderly are accompanied by discomfort and disability. A variety of systems are developed and distributed to overcome them. The electric wheelchair is an electric motorized system for people who can not manipulate a manual wheelchair. In this paper, we propose an autonomous driving platform for an electric wheelchair. Here we use QR (Quick Response) code for self-localization. We also present real test results of the proposed system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.457-462
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• 2005

Industrial and economical importance of CP(Cellular Phone) is growing rapidly. Combined with IT technology, CP is currently one of the most attractive technologies for all. However, unless we find a breakthrough to the technology, its growth may slow down soon. RT(Robot Technology) is considered one of the most promising next generation technology. Unlike the industrial robot of the past, today's robots require advanced technologies, such as soft computing, human-friendly interface, interaction technique, speech recognition, object recognition, and many others. In this study, we present a new technological concept named RCP(Robotic Cellular Phone), which combines RT & CP, in the vision of opening a new direction to the advance of CP, IT, and RT all together. RCP consists of 3 sub-modules. They are $RCP^{Mobility}$, $RCP^{Interaction}$, and $RCP^{Interaction}$. $RCP^{Mobility}$ is the main focus of this paper. It is an autonomous navigation system that combines RT mobility with CP. Through $RCP^{Mobility}$, we should be able to provide CP with robotic functionalities such as auto-charging and real-world robotic entertainments. Eventually, CP may become a robotic pet to the human being. $RCP^{Mobility}$ consists of various controllers. Two of the main controllers are trajectory controller and self-localization controller. While Trajectory Controller is responsible for the wheel-based navigation of RCP, Self-Localization Controller provides localization information of the moving RCP. With the coordinate information acquired from RFID-based self-localization controller, Trajectory Controller refines RCP's movement to achieve better RCP navigations. In this paper, a prototype system we developed for $RCP^{Mobility}$ is presented. We describe overall structure of the system and provide experimental results of the RCP navigation.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.258-260
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• 2005

We describe a method for localizing a mobile robot in the working environment using a vision system and VRML. The robot identifies landmarks in the environment and carries out the self-positioning. The image-processing and neural network pattern matching technique are employed to recognize landmarks placed in a robot working environment. The robot self-positioning using vision system is based on the well-known localization algorithm. After self-positioning, 2D scene is overlaid with VRML scene. This paper describes how to realize the self-positioning and shows the result of overlaying between 2D scene and VRML scene. In addition we describe the advantage expected from overlapping both scenes.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.312-319
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• 2009

This paper proposes a low-complexity indoor localization method of mobile robot under the dynamic environment by fusing the landmark image information from an ordinary camera and the distance information from sensor nodes in an indoor environment, which is based on sensor network. Basically, the sensor network provides an effective method for the mobile robot to adapt to environmental changes and guides it across a geographical network area. To enhance the performance of localization, we used an ordinary CCD camera and the artificial landmarks, which are devised for self-localization. Experimental results show that the real-time localization of mobile robot can be achieved with robustness and accurateness using the proposed localization method.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.116-124
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• 2011

A service robot can identify its own position relative to landmarks, the locations of which are known in advance. The main contribution of this research is that it gives various ways of making the self-localizing error smaller by referring to special landmarks which are developed as high gain reflection material and coded array associations. In this paper, the authors propose a set of indices to evaluate the accuracy of self-localizing methods using the selective reflection landmark and infrared projector, and the indices are derived from the sensitivity enhancement using 3D distortion calibration of camera. And then, the accurarcy of self-localizing a mobile robot with landmarks based on the indices is evaluated, and a rational way to minimize to reduce the computational cost of selecting the best self-localizing method. The simulation results show a high accuracy and a good performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.306-311
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• 2003

This paper presents a novel localization paradigm for mobile robots based on artificial and natural landmarks. A model-based object recognition method detects natural landmarks and conducts the global and topological localization. In addition, a metric localization method using artificial landmarks is fused to complement the deficiency of topology map and guide to action behavior. The recognition algorithm uses a modified local Zernike moments and a probabilistic voting method for the robust detection of objects in cluttered indoor environments. An artificial landmark is designed to have a three-dimensional multi-colored structure and the projection distortion of the structure encodes the distance and viewing direction of the robot. We demonstrate the feasibility of the proposed system through real world experiments using a mobile robot, KASIRI-III.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.749-757
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• 2001

We present a simple artificial landmark model and robust landmark tracking algorithm for mobile robot localization. The landmark model, consisting of symmetric and repetitive color patches, produces color histograms that are invariant under the geometric and photometric distortions. A stochastic approach based on the CONDENSATION tracks the landmark model robustly even under the varying illumination conditions. After the landmark detection, relative position of the mobile robot to the landmark is calculated. Experimental results show that the proposed landmark model is effective and can be detected and tracked in a clustered scene robustly. With the tracked single landmark, we extract geometrical information than achieve accurate localization.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2581-2584
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• 2003

In this paper, we propose a self-localization algorithm using vertical line segments. Indoor environment is consist of horizontal and vertical line features such as doors, furniture, and so on. From the input image, vertical line edges are detected by an edge operator, Then, line segments are obtained by projecting edge image vertically and detecting local maximum from the projected histogram. From the relation of horizontal position of line segments and the location of the robot, nonlinear equations are come out Localization is done by solving the equations by using Newton's method. Experimental results show that the proposed algorithm using one camera is simple and applicable to indoor environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5299-5320
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• 2019

Interest in self-driving vehicle research has been rapidly increasing, and related research has been continuously conducted. In such a fast-paced self-driving vehicle research area, the development of advanced technology for better convenience safety, and efficiency in road and transportation systems is expected. Here, we investigate research in self-driving vehicles and analyze the main technologies of driverless car software, including: technical aspects of autonomous vehicles, traffic infrastructure and its communications, research techniques with vision recognition, deep leaning algorithms, localization methods, existing problems, and future development directions. First, we introduce intelligent self-driving car and road infrastructure algorithms such as machine learning, image processing methods, and localizations. Second, we examine the intelligent technologies used in self-driving car projects, autonomous vehicles equipped with multiple sensors, and interactions with transport infrastructure. Finally, we highlight the future direction and challenges of self-driving vehicle transportation systems.