• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.112-121
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• 2021

Unlike a typical small-sized robot navigating in a free space, an autonomous vehicle has to travel in a designated road which has lanes to follow and traffic rules to obey. High-Definition (HD) maps, which include road markings, traffic signs, and traffic lights with high location accuracy, can help an autonomous vehicle avoid the need to detect such challenging road surroundings. With space constraints and a pre-built HD map, a new type of path planning algorithm can be conceived as a substitute for conventional grid-based path planning algorithms, which require substantial planning time to cover large-scale free space. In this paper, we propose an obstacle-avoiding, cost-based planning algorithm in a continuous space that aims to pursue a globally-planned path with the help of HD map information. Experimentally, the proposed algorithm is shown to outperform other state-of-the-art path planning algorithms in terms of computation complexity in a typical urban road setting, thereby achieving real-time performance and safe avoidance of obstacles.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.890-903
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• 2017

The problem of determining a smooth and collision-free path with maximum possible speed for a Mobile Robot (MR) which is chasing a moving target in a dynamic environment is addressed in this paper. Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. This paper presents GNP-RL based on predicting collision positions as a first attempt to apply it for MR navigation in dynamic environment. The combination between features of the proposed collision prediction and that of GNP-RL provides safe navigation (effective obstacle avoidance) in dynamic environment, smooth movement, and reducing the obstacle avoidance latency time. Simulation in dynamic environment is used to evaluate the performance of collision prediction based GNP-RL compared with that of two state-of-the art navigation approaches, namely, Q-Learning (QL) and Artificial Potential Field (APF). The simulation results show that the proposed GNP-RL outperforms both QL and APF in terms of smooth movement and safer navigation. In addition, it outperforms APF in terms of preserving maximum possible speed during obstacle avoidance.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.35-43
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• 2019

This paper describes the improved environment recognition algorithms using some type of sensors like LiDAR and cameras. Additionally, integrated control algorithm for an autonomous vehicle is included. The integrated algorithm was based on C++ environment and supported the stability of the whole driving control algorithms. As to the improved vision algorithms, lane tracing and traffic sign recognition were mainly operated with three cameras. There are two algorithms developed for lane tracing, Improved Lane Tracing (ILT) and Histogram Extension (HIX). Two independent algorithms were combined into one algorithm - Enhanced Lane Tracing with Histogram Extension (ELIX). As for the enhanced traffic sign recognition algorithm, integrated Mutual Validation Procedure (MVP) by using three algorithms - Cascade, Reinforced DSIFT SVM and YOLO was developed. Comparing to the results for those, it is convincing that the precision of traffic sign recognition is substantially increased. With the LiDAR sensor, static and dynamic obstacle detection and obstacle avoidance algorithms were focused. Therefore, improved environment recognition algorithms, which are higher accuracy and faster processing speed than ones of the previous algorithms, were proposed. Moreover, by optimizing with integrated control algorithm, the memory issue of irregular system shutdown was prevented. Therefore, the maneuvering stability of the autonomous vehicle in severe environment were enhanced.

• 재활복지
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• v.17 no.4
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• pp.383-399
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• 2013

The purpose of this study was to comparison the effects of aqua-and-land based obstacle training on balance of chronic stroke patients. Subjects were randomly divided into an aqua group(n=15) and d land group(n=15). Both group received obstacle training for 40 minutes, 3 times a week during 12 weeks. Static balance was assessed by measuring the mean velocity of mediolateral, anteroposterior and sway area with the eyes open using Good Balance System. Dynamic balance was assessed by measuring Functional Reaching Test(FRT) and the Timed Up and Go test(TUG). Following the intervention, both groups showed significant changes static balance(the mean velocity of mediolateral, anteroposterior and sway area) and dynamic balance(FRT and TUG). There were significant difference in the mean velocity of mediolateral, anteroposterior, sway area, FRT and TUG between the two groups after the interventions. The results of this study suggest that the aqua group and land group were increase balance functions of chronic stroke patients. The aqua group was significantly higher than the land group for patients with chronic stroke patients. We hope that aquatic training can be useful for patients with chronic stroke patients to improve balance functions and the aqua training research for improve balance functions will be conducted continuously.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.3
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• pp.301-309
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• 1999

Real-time kinematic (RTK) GPS surveying which allows centimeter level accuracy of three-dimensional coordinates without post-processing has become recognized as a major advance in GPS technology. Employing On-The-Fly initialization technique, the RTK system can escape from cycle slip problems that have affected as a main obstacle factor in traditional kinematic and static approaches. The objective of this research was to evaluate accuracy and effectiveness of the RTK-GPS surveying. First, the continuous RTK observation of a base line was conducted for the purpose of finding out the repeatability of the RTK surveying and the results which were then compared against results from static surveying showed RMS errors of $\pm{3mm}\;and\;\pm{13mm}$ for their respective horizontal and vertical components. On a test network of 30 stations covering the small area, the results of RTK testing were compared against those from not only post-processing kinematic and rapid-static surveyings but conventional surveyings and also the efficiency of RTK were analyzed. In addition, geoid heights which were derived by combination of GPS and spirit leveling about all of the points within the network were compared against those derived by the PNU95 and EGM96 models respectively.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.918-925
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• 2017

This paper presents a path planning problem for multi-robot system in the environment with dynamic obstacles. In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly, a navigation method based on fuzzy logic controllers has been developed by using proximity sensors. There are two kinds of fuzzy controllers developed in this work, one is used for obstacle avoidance and the other is used for orientation to the target. Both static and dynamic obstacles are included in the environment and the dynamic obstacles are defined with no type of restriction of direction and velocity. Here, the environment is unknown for all the robots and the robots should detect the surrounding information only by the sensors installed on their bodies. The simulation results show that the proposed method has a positive effectiveness for the path planning problem.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.8
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• pp.2593-2600
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• 1996

A modified k-$\varepsilon$ turbulence model having a generality is proposed in the present study, in which the constant $C_{\varepsilon2}$in the $\varepsilon$-equation is simply changed as a functional form of a new parameter both satisfying the tensor invariant condition and representing the extra straining effect on complex shear flows. With this model turbulent shear flows over two-dimensional obstacles placed in a channel are numerically studied for different blockage ratios and aspect ratios. Comparing with the available experimental data, the predicted results with the present model provide definite improvements over the standard model's results and work fairly well with the experimental data on the size of the recirculation zone, as well as mean velocity, wall static pressure, turbulent kinetic energy and Reynolds stresses.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.100-108
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• 2002

A fuzzy logic for collision avoiding navigation of marine vehicles is proposed in this paper. VFF(Virtual Force Field) method, which is used widely in the field of mobile robots, is modifiel to apply to marine vehicles. The method is named MVFF (Modified Virtual Force Field) mothod. The MVFF consists of the determination of the heading angles far track-keeping mode ($\psi_{ca}$)and collision avoidance mode ($\psi_{ca}$). The operator can choose the pattern of the track-keeping mode in the proposed algorithm. The collision avoidance algorithm can handle static and/or moving obstacles. These functons are implemented using fuzzy logic. Various simulation results verify the proposed alogorithm.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.633-635
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• 1999

In this paper, we propose a new method of path planning for multiple mobile robot in dynamic environment. To search the optimal path, multiple mobile robot is always generating path with static and dynamic obstacles avoidance from start point to goal point. The purpose of this paper is to design an optimal path for the mobile robot.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.4
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• pp.135-141
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• 2008

Independent suspension axle and final reduction gear for special-purpose vehicles such as a armored vehicles are almost imported in Germany etc. so, developing them is necessary to save cost. In severe condition (open fields, water surface driving, obstacle pass), special-purpose vehicles must work well. Drop box, axle and final reduction gear performed static analysis. We know that is possible weight reduction. The purpose of this paper is to find out the optimal shape of final reduction gear's case by means of response surface methodology. The response surface method is the statistical method which can be applied to the non-sensitivity based optimization. The response surface which is constructed by the least square method contains only the polynomial terms so that the global maximum and minimum points are easily obtained.