• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.599-604
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• 2008

Recently, many researches for autonomous mobile system have been proposed, which can recognize surrounded environment and navigate to destination without outside intervention. The basic sufficient condition for the autonomous mobile system is to navigate to destination safely without accident. In this paper, we propose a path planning method in local region for safe navigation of autonomous system through evaluation of the road surface distortion(damaged/deformed road, unpaved road, obstacle and etc.). We use laser distance sensor to get the information on the road surface distortion and apply image binalization method to evaluate safe region in the detected local region. We show the validity of the proposed method through the computer simulation based on the artificial local road map.

• Journal of Biosystems Engineering
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• v.20 no.3
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• pp.226-235
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• 1995

An unmanned speed sprayer was developed using a remote control and an inductive cable guidance systems to protect operators and environment from hazardous pesticides. The sprayer consists of a remote control system, an induction system, obstacle detectors, control actuators and an one-chip microcomputer. The sprayer can be operated by the induction guidance and/or remote control. The following summarize characteristics of the developed speed sprayer. 1) Both the remote control and the induction guidance operation were possible with the developed speed sprayer. 2) Sixteen functions of the forwarding, backing, halting, steering, 3-way valve for nozzles and fan operating etc. were utilized on the remote control system. 3) It was concluded that the DTMF method, having less transmitting error, performed better than the FSK method for an agricultural remote controller. A radio station may be necessary. 4) The digital inductive guidance system, consisting of five low-impedance detection coils and a window comparator circuit, performed better than the analog detecting system, guiding route using inductive voltage differential from tow detection coils.

• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.1-10
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• 2011

The spectrum sensing is one of the fundamental functions to realize the cognitive radios. One of problems in the spectrum sensing is that the performance of spectrum sensing can be degraded due to fading and shadowing. In order to overcome the problem, cooperative spectrum sensing method is proposed, which uses a distributed detection model and can increase sensing performance. However, the performance of cooperative spectrum sensing can be still affected by the interference factors such as obstacle and malicious user. Especially, most of cooperative spectrum sensing methods only considered the stationary primary user. In the ubiquitous environment, however the mobile primary users should be considered. In order to overcome the aforementioned problem, in this paper we propose a robust spectrum detection method based on localization where we estimate the location of the mobile primary user, and then based on the location and transmission range of primary user we detect interference users if there are, and then the local sensing reporting from detected interference users are excluded in the decision fusion process. Through simulation, it is shown that the sensing performance of the proposed scheme is more accurate than that of conventional other schemes

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.843-850
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• 2003

Script viruses are easy to make a variation because they can be built easily and be spread in text format. Thus signature-based method has a limitation in detecting script viruses. In a consequence, many researches suggest simple heuristic methods, but high false-positive error is always being an obstacle. In order to overcome this problem, our previous study concentrated on analyzing data flow of codes and has low-false positive error, but still could not detect a polymorphic virus because polymorphic virus loads self body and changes it before make a descendent. We suggest a heuristic detection method which expands the detection range of previous method to include polymorphic script viruses. Expanded data flow analysis heuristic has an expanded grammar to detect Polymorphic copy Propagation. Finally, we will show the experimental result for the effectiveness of suggested method.

• Smart Structures and Systems
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• v.31 no.5
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.5
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• pp.647-653
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• 2017

In this paper, we deal with the experimental verification of 1D virtual force field algorithm based reflexive local path planning on uneven and dusty environment. The existing obstacle detection method on uneven and dusty environment and 1D virtual force field based reflexive local path planning algorithm simply are introduced. Although the 1D virtual force field algorithm is verified by various simulations, additional efforts are needed to verify this algorithm in the real-world. The introduced methods are combined with each other, installed to real mobile platforms and verified by various real experiments.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.4 no.2
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• pp.24-33
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• 1993

In indoor radio systems, vehicular communication systems, and land mobile systems, a very important problem is that of maintaing stable communications at all locations. Therefore solutions for the indoor propagation problem are an important aspects of the mobile communication system. Leaky coaxial cables finding increasing use in communications systems involving mines, tunnels, railroads, and highways, and in new obstacle detection, or guided radar, schemes for ground transpor- tation and perimeter surveilance. In this paper a leaky coaxial cable having periodic slots in the outer conductor is described to obtain the propagation modes in the various environments. We use an essentric cylindrical model to develop the theory for surface-wave propagation on the cable. Numerical Results are also included for the propagation constants, field distribution and impedance as functions of various parameters. First, we derive the electromagnetic equation for leaky coaxial cable having periodic slots using mode-matching method and Floguet's theorem, and then find various modes, propagation constants, field distribution, etc.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.55-59
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• 2008

For effective mobility control of UGV(unmanned ground vehicle), the terrain cover classification is an important component as well as terrain geometry recognition and obstacle detection. The vision based terrain cover classification algorithm consists of pre-processing, feature extraction, classification and post-processing. In this paper, we present a method to classify terrain covers based on the color and texture information. The color space conversion is performed for the pre-processing, the wavelet transform is applied for feature extraction, and the SVM(support vector machine) is applied for the classifier. Experimental results show that the proposed algorithm has a promising classification performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.285-292
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• 2018

In this paper, we propose a distributed search of a cluster robot using tree structure in an unknown environment. In the proposed method, the cluster robot divides the unknown environment into 4 regions by using the LRF (Laser Range Finder) sensor information and divides the maximum detection distance into 4 regions, and detects feature points of the obstacle. Also, we define the detected feature points as Voronoi Generators of the Voronoi Diagram and apply the Voronoi diagram. The Voronoi Space, the Voronoi Partition, and the Voronoi Vertex, components of Voronoi, are created. The generated Voronoi partition is the path of the robot. Voronoi vertices are defined as each node and consist of the proposed tree structure. The root of the tree is the starting point, and the node with the least significant bit and no children is the target point. Finally, we demonstrate the superiority of the proposed method through several simulations.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.696-704
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• 2011

In this paper, we propose a mobile robot navigation algorithm using data fusion of a monocular camera and ultrasonic sensors. Threshold values for binary image processing are generated by a fuzzy inference method using image data and data of ultrasonic sensors. Threshold value variations improve obstacle detection for mobile robot to move to the goal under poor illumination environments. Obstacles detected by data fusion of camera and ultrasonic sensors are expressed on the grid map and avoided using the circular planning algorithm. The performance of the proposed method is evaluated by experiments on the Pioneer 2-DX mobile robot in the indoor room with poor lights and a narrow corridor.