• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.499-507
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• 2018

Autonomous Underwater Vehicle (AUV), which are becoming more and more important in ocean exploitation tasks, needs energy conservation urgently when sailing the complex mission path in long time cruise. As hull lines optimization design becomes the key factor, which closely related with resistance, in AUV preliminary design stage, uncertainty parameters need to be considered seriously. In this research, Myring axial symmetry revolution body with parameterized expression is assumed as AUV hull lines, and its travelling resistance is obtained via modified DATCOM formula. The problems of AUV hull lines design for the minimum travelling resistance with uncertain parameters are studied. Based on reliability-based optimization design technology, Design For Six Sigma (DFSS) for high quality level is conducted, and is proved more reliability for the actual environment disturbance.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.3
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• pp.281-292
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• 2019

This paper proposed a new technology to control a path forging parts in limited narrow space of manufacturing process automation for smart factory. In the motion control, we adapted the obstacle avoidance technology based on ultrasonic sensors. The new motion control performance test for a mobile robot is experimented in narrow space environments. The travelling path control is performed by a fuzzy control logic. which plays a role for selecting an appropriate behavior in accordance with the situation in the vicinity of the mobile robot. Ultrasonic sensors installed at the front face of the mobile robot are used. In order to update the current position and heading angle of the mobile robot, a new approch is adapted. The reliability is illustrated by simulation and experiments.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.1
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• pp.10-17
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• 2015

We describe a research about remote control of mobile robot based on voice command in this paper. Through real-time remote control and wireless network capabilities of an unmanned remote-control experiments and Home Security / exercise with an unmanned robot, remote control and voice recognition and voice transmission are possible to transmit on a PC using a microphone to control a robot to pinpoint of the source. Speech recognition can be controlled robot by using a remote control. In this research, speech recognition speed and direction of self-driving robot were controlled by a wireless remote control in order to verify the performance of mobile robot with two drives.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.909-915
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• 2008

Recently, the interests in the development and application of unmaned robots are increasing in various fields including surveillance and reconnaissance, planet exploration, and disaster relief. Unmaned robots are usually controlled from distance using radio communications but they should be equipped with an autonomous travelling function to cope with unexpected terrains and obstacles. This means that they should be able to evaluate terrain's characteristics quantitatively using mounted sensors so as to traverse harsh natural terrains autonomously. For this purpose, this paper presents a method for extracting terrain information, that is, slope and roughness from elevation maps as a prior step of traversability analysis. Slope is extracted using the curve fitting based on the least squares method and roughness using three metrics and their weighted average. The effectiveness of the proposed method is verified on both a fractal map and the world model map of a real terrain.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.233-236
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• 2008

Recently, the development and application of unmaned robots are increasing in various fields including surveillance and reconnaissance, planet exploration and disaster relief. Unmaned robots are usually controlled from distance using radio communications but they should be equipped with autonomous travelling function to cope with unexpected terrains and obstacles. This means that unmanned robots should be able to evaluate terrain's characteristics quantitatively using mounted sensors so as to traverse harsh natural terrains autonomously. For this purpose, this paper presents an algorithm for extracting terrain information from elevation maps as an early step of traversability analysis. Slope and roughness information are extracted from a world terrain map based on least squares method and fractal theory, respectively. The effectiveness of the proposed algorithm is verified on both fractal and real terrain maps.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.323-330
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• 2020

This paper proposes the road roughness based Braking Pressure Calculation System(BPCS) for an Autonomous Vehicle Stability. The system consists of an image normalization module that processes the front image of a vehicle to fit the input of the random forest, a Random Forest based Road Roughness Classification Module that distinguish the roughness of the road on which the vehicle is travelling by using the weather information and the front image of a vehicle as an input, and a brake pressure control module that modifies a friction coefficient applied to the vehicle according to the road roughness and determines the braking strength to maintain optimal driving according to a vehicle ahead. To verify the efficiency of the BPCS experiment was conducted with a random forest model. The result of the experiment shows that the accuracy of the random forest model was about 2% higher than that of the SVM, and that 7 features should be bagged to make an accurate random forest model. Therefore, the BPCS satisfies both real-time and accuracy in situations where the vehicle needs to brake.