• ETRI Journal
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• v.43 no.4
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• pp.580-593
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• 2021

When operating in confined spaces or near obstacles, collision-free path planning is an essential requirement for autonomous exploration in unknown environments. This study presents an autonomous exploration technique using a carefully designed collision-free local planner. Using LiDAR range measurements, a local end-point selection method is designed, and the path is generated from the current position to the selected end-point. The generated path showed the consistent collision-free path in real-time by adopting the Euclidean signed distance field-based grid-search method. The results consistently demonstrated the safety and reliability of the proposed path-planning method. Real-world experiments are conducted in three different mines, demonstrating successful autonomous exploration flights in environment with various structural conditions. The results showed the high capability of the proposed flight autonomy framework for lightweight aerial robot systems. In addition, our drone performed an autonomous mission in the tunnel circuit competition (Phase 1) of the DARPA Subterranean Challenge.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.12
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• pp.61-70
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• 2005

In this paper, we propose an efficient global placement algorithm which is an enhanced version of Hybrid Placer$^{[25]}$, a standard cell placement tool, which uses a middle-down approach. Combining techniques used in the well-known partitioner hMETIS and the RBLS(Relaxation Based Local Search) in Hybrid Placer improves the quality of global placements. Partitioning techniques of hMETIS is applied in a top-down manner and RBLS is used in each level of the top-down hierarchy to improve the global placement. The proposed new approach resolves the problem that Hybrid Placer seriously depends on initial placements and it speeds up without deteriorating the placement quality. Experimental results prove that solutions generated by the proposed method on the MCNC benchmarks are comparable to those by FengShui which is a well known placement tool. Compared to the results of the original Hybrid Placer, new method is 5 times faster on average and shows improvement on bigger circuits.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1142-1147
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• 2015

As a method to increase the scalability and efficiency of wireless sensor networks, a scheme to construct networks hierarchically has received considerable attention among researchers. Researches on the methods to construct wireless networks hierarchically have been conducted focusing on how to select nodes such that they constitute a backbone network of wireless network. Nodes comprising the backbone network should be connected themselves and can cover other remaining nodes. A problem to find the minimum number of nodes which satisfy these conditions is known as the minimum connected dominating set (MCDS) problem. The MCDS problem is NP-hard, therefore there is no efficient algorithm which guarantee the optimal solutions for this problem at present. In this paper, we propose a novel multi-start local search algorithm to solve the MCDS problem efficiently. For the performance evaluation of the proposed method, we conduct extensive experiments and report the results.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.3
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• pp.213-217
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• 2014

A hybrid search method based on the artificial bee colony algorithm (ABCA) with harmony search (HS) is suggested for finding a global solution in the field of optimization. Three cases of the suggested algorithm were examined for improving the accuracy and convergence rate. The results showed that the case in which the harmony search was implemented with the onlooker phase in ABCA was the best among the three cases. Although the total computation time of the best case is a little bit longer than the original ABCA under the prescribed conditions, the global solution improved and the convergence rate was slightly faster than those of the ABCA. It is concluded that the suggested algorithm improves the accuracy and convergence rate, and it is expected that it can effectively be applied to optimization problems with many design variables and local solutions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1254-1259
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• 2010

In this paper, Low Computational Adaptive Expanded Block Search Motion Estimation Method is proposed. Proposed method classifies ME blocks as Average Motion Block(AMB) and Local Motion Block(LMB) according to correlation of reference frame. It could reduce the computational complexity with performing Modified Fast Search(MFS). And accuracy of MV is also increased by 4 sub-blocks on LMB and Block Expansion(BE). The experimental results show that the proposed method has better performance that increased 1.8dB than Diamond Search and 0.6dB than Full Search with 7.5 % computation of Full Search. The proposed method could be applied to video compression and Frame Rate Conversion(FRC).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9B
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• pp.1299-1307
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• 2001

고정된 패턴을 사용하는 기존의 고속 블록기반 움직임 추정법에서는 국소 최소해로 고립될 가능성이 있을 뿐만 아니라, 여러 움직임이 공존하는 움직임 경계에서 정확한 움직임의 추정이 어렵다는 문제점을 가지고 있다. 이러한 문제점을 극복하기 위하여 본 논문에서는 탐색점의 수를 줄이는 동시에 국소 최소해로의 고립을 피하기 위하여 탐색 후보영역을 적용한 다중 국소 탐색법(multiple local search method : MLSM)을 제안한다. 또한, 블록 내의 움직임 영역별 정합오차의 최소편차를 고려하는 새로운 정합함수를 제안함으로써 움직임 경계에서 움직임 벡터추정의 부정확성과 움직임 보상영상에서의 화질저하문제를 개선하고자 한다. 실험결과, 제안한 방법은 기존의 방법에 비해 움직임 경계에서의 추정에서 우수한 결과를 보였으며, PSNR에 대해서도 전역탐색법과 유사한 결과를 얻을 수 있었고, 움직임 보상결과, 움직임 경계부근에서의 향상된 화질을 얻을 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.490-490
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• 2000

Parallel genetic algorithms are particularly easy to implement and promise substantial gains in performance. Its basic idea is to keep several subpopulations that are processed by genetic algorithms. Furthermore, a migration mechanism produces a chromosome exchange between subpopulation. In this paper, a new selection method based on non-linear fitness assignment presented. The use of proposed ranking selection permits higher local exploitation search, where the diversity of populations is structure. Experimental results show that the relation between local-global search balance and the probabilities of reaching a desired solution.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.45-51
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• 2011

This paper proposes a method to accelerate the evolution speed of individuals through hybrid reproduction of monogenesis and gamogenesis. Monogenesis as a reproduction method that bacteria or monad without sexual distinction divide into two individuals has an advantage for local search and gamogenesis as a reproduction method that individuals with sexual distinction mate and breed the offsprings has an advantages for keeping the diversity of individuals. These properties can be properly used for improvement of evolution speed of individuals in genetic algorithms. In this paper, we made relatively good individuals among selected parents to do monogenesis for local search and forced relatively bad individuals among selected parents to do gamogenesis for global search by increasing the diversity of chromosomes. The mutation probability for monogenesis was set to a lower value than that of original genetic algorithm for local search and the mutation probability for gamogenesis was set to a higher value than that of original genetic algorithm for global search. Experimental results with four function optimization problems showed that the performances of three functions were very good, but the performances of fourth function with distributed global optima were not good. This was because distributed global optima prevented individuals from steady evolution.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.116-124
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• 1999

In most conventional design optimization of dynamic system, design sensitivities are utilized. However, design sensitivities based optimization method has numbers of drawback. First, computing design sensitivities for dynamic system is mathematically difficult, and almost impossible for many complex problems as well. Second, local optimum is obtained. On the other hand, Genetic Algorithm is the search technique based on the performance of system, not on the design sensitivities. It is the search algorithm based on the mechanics of natural selection and natural genetics. GA search, differing from conventional search techniques, starts with an initial set of random solutions called a population. Each individual in the population is called a chromosome, representing a solution to the problem at hand. The chromosomes evolve through successive iterations, called generations. As the generation is repeated, the fitness values of chromosomes were maximized, and design parameters converge to the optimal. In this study, Genetic Algorithm is applied to the actual dynamic optimization problems, to determine the optimal design parameters of the dynamic system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.229-238
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• 2007

This study was intended to point out the limit of existing digital content-centered studies, or approaches from the viewpoint of the supplier and in the aspect of business profit model and find ways to assess the quality of digital content, considering the characteristics of digital content. For this, the study is to apply value innovation strategy to digital content assessment, to analyze the applicability, and to propose a new and practical framework for digital content assessment method. To this end, this study selected the global No. 1 search service provider Google and local portal site Naver search service. The study on assessment factors by value innovation strategy was based on existing literature, while user-value elements in that respect were confined to information quality, interactivity, communication, interactive storytelling, and usability. This study objectified the relation with the value innovation strategic analysis, through qualitative and quantitative analyses on value elements of search service users.