• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.15-20
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• 2004

Inclined surface milling in the mould and die industries is one of the most commonly needed cutting process. For the variety and complexity of cutting characteristics in various cutting condition, it is difficult to select a optimal tool path orientation. The comparative results through FFT analysis in this study provide a guideline for the selection tool path orientation.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.72-75
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• 1988

Due to the fact that the set point regulation scheme by the variable structure control method concerns only the initial and final locations of a manipulator, many constraints may exist in the application of path tracking with obstracle avoidance. The variable structure parameter should be selected in the trajectory planning step by satisfying the constraints of the travel time and the path deviations This paper presents the selection algorithm of the variable structure parameters with the constraints of the system dynamics and the travel time and the path deviation. This study makes unify the trajectory planning and tracking control using the variable structure control method.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.904-914
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• 2008

An action-selection-mechanism(ASM) has been proposed to work as a fully connected finite state machine to deal with sequential behaviors as well as to allow a state in the task program to migrate to any state in the task, in which a primitive node in association with a state and its transitional conditions can be easily inserted/deleted. Also, such a primitive node can be learned by a shortest path-finding-based reinforcement learning technique. Specifically, we define a behavioral motivation as having state-dependent value as a primitive node for action selection, and then sequentially construct a network of behavioral motivations in such a way that the value of a parent node is allowed to flow into a child node by a releasing mechanism. A vertical path in a network represents a behavioral sequence. Here, such a tree for our proposed ASM can be newly generated and/or updated whenever a new behavior sequence is learned. To show the validity of our proposed ASM, experimental results of a mobile robot performing the task of pushing- a- box-in to- a-goal(PBIG) will be illustrated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2372-2380
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• 2015

In this paper, we propose frequency allocation and path selection scheme in underlay cognitive radio (CR) networks using network coding. In the proposed scheme, we choose the path with consideration of network coding and interference temperature in underlay CR networks and propose an optimization problem to maximize the system throughput of secondary users (SUs). Then, we represent the proposed optimization problem as the multi-dimensional multiple-choice knapsack problem and give the theoretical upper bound for the system throughput of SUs by using linear programming. Finally, we compute the system throughput of SUs by using brute-force search (BFS) and link quality first (LQF) scheme in underlay CR networks. Simulation results show that the system throughput of SUs with BFS is higher than that with LQF in underlay CR networks with and without application of network coding, respectively.

• Journal of Ginseng Research
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• v.42 no.2
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• pp.158-164
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• 2018

Background: The study was carried out to assess the genetic variability present in ashwagandha and to examine the nature of associations of various traits to the root yield of the plant. Methods: Fifty-three diverse genetic stocks of ashwagandha (Withania somnifera) were evaluated for 14 quantitative characteristics. Analysis of variance, correlation, and path coefficient analysis were performed using the mean data of 2 years. Results: Analysis of variance revealed that the genotypes differed significantly for all characteristics studied. High heritability in conjunction with high genetic advance was observed for fresh root weight, 12 deoxywithastramonolide in roots, and plant height, which indicated that selection could be effective for these traits. Dry root weight has a tight linkage with plant height and fresh root weight. Further, in path coefficient analysis, fresh root weight, total alkaloid (%) in leaves, and 12 deoxywithastramonolide (%) in roots had the highest positive direct effect on dry root weight. Conclusion: Therefore, these characteristics can be exploited to improve dry root weight in ashwagandha genotypes and there is also scope for the selection of promising and specific chemotypes (based on the alkaloid content) from the present germplasm.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.445-453
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• 2016

Fixed robust routing is attracting attention as routing that achieves high robustness against changes in traffic patterns without conducting traffic measurement and performing dynamic route changes. Fixed robust routing minimizes the worst-case maximum link load by distributing traffic of every source-destination (s-d) router pair onto multiple candidate paths (multipath routing). Multipath routing, however, can result in performance degradation of Transmission Control Protocol (TCP) because of frequent out-of-order packet arrivals. In this paper, we first investigate the influence of multipath routing on TCP performance under fixed robust routing with a simulation using ns-2. The simulation results clarify that TCP throughput greatly degrades with multipath routing. We next propose a candidate path selection method to improve TCP throughput while suppressing the worst-case maximum link load to less than the allowed level under fixed robust routing. The method selects a single candidate path for each of a predetermined ratio of s-d router pairs in order to avoid TCP performance degradation, and it selects multiple candidate paths for each of the other router pairs in order to suppress the worst-case maximum link load. Numerical examples show that, provided the worst-case maximum link load is less than 1.0, our proposed method achieves about six times the TCP throughput as the original fixed robust routing.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.249-251
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• 2005

In this paper, an algorithm of path planning and obstacle avoidance for mobile robot is proposed. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors. By processing assigned numbers all regions are covered and then the path from start to destination is selected by these numbers. The RAS has an advantage of fast planning because of simple operations. This implies that new path selection may be possible within a short time and helps a robot to avoid obstacles in any direction. The algorithm can be applied to unknown environments. When moving obstacles appear, a mobile robot avoids obstacles reactively. then new path is selected by RAS.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.726-732
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• 2013

It is required for UGV(Unmanned Ground Vehicle) to have a LPP(Local Path Plan) component which generate a local path via the center of road by analyzing binary map to travel autonomously unpaved road in rough environment. In this paper, we present the method of boundary estimation for unpaved road and a local path planning method based on RANGER algorithm using the estimated boundary. In specially, the paper presents an approach to estimate road boundary and the selection method of candidate path to minimize the problem of zigzag driving based on Bayesian probability reasoning. Field test is conducted with scenarios in rough environment in which bush, tree and unpaved road are included and the performance of proposed method is validated.

• 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 Korea Multimedia Society
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• v.25 no.8
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• pp.1007-1021
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• 2022

Autonomous driving of unmanned aerial vehicles may have to pay expensive cost to create and switch new routes if unexpected obstacles exist or local map updates occured by the control system due to incorrect route information. Integrating digital twins into the path-following process requires more computing resources to quickly switch the wrong path to an alternative path, but it can quickly update the path during flight. In this study, we design a DEVS-based simulation environment which can modify optimized paths through short-term simulation of multi-virtual UAVs for applying digital twin concepts to path follow. Through simulation, we confirmed the possibility of increasing the mission stability of UAV.