• Journal of the HCI Society of Korea
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• v.5 no.2
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• pp.25-31
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• 2010

This paper proposes a hybrid tour path planning system for multiple visitors in a museum. The proposed path planning system merges individual user profiles into a group profile by exploiting the multiplicative utilization algorithm. It then generates a tour path for the users based on mixed initiative decision of the system and the involved visitors. It automatically selects visiting sites when group users have highly similar preferences while it asks users to select their appropriate visiting sites among available sites when their preferences are different. We developed the hybrid path planning system based on a tabletop display and evaluated it with four different exhibition settings and 11 participants. We found that the mixed decision of the system and users was useful in building a tour path for a group of visitors.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.4
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• pp.1-9
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• 2003

Many CDMA systems provide pilot channels in order to help channel estimation process. Especially in wideband CDMA systems, the number of receive diversity paths can be large due to small chip duration and high multi-path resolution capability. Hence, the received signal power of each path is small for a given total SNR (signal-to-noise ratio) and the pilot power of each path may not be sufficiently large for accurate channel estimation. When the pilot power is small, one can use decision-directed channel estimation to utilize more energy of the received data. However, the decision errors can deteriorate the quality of decision-directed channel estimation. This paper proposes a novel channel estimation method that optimally utilizes receiver decisions as well as pilot symbols with the help of estimated SER (symbol error rate) and SNR. The proposed method computes two channel estimates using the pilot and the data channel filters and optimally combines them. The simulation results show that the proposed method is robust and outperforms the conventional pilot-symbol-aided channel estimation method.

• Journal of the military operations research society of Korea
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• v.17 no.2
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• pp.72-89
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• 1991

In transportation network problems, it is often desirable to select multiple number of the shortect paths. On problems of finding these paths, algorithms have been developed to choose single shortest path, k-shortest paths and k-shortest paths via p-specified nodes in a network. These problems consider the time as the main factor. In wartime, we must consider availability as well as time to determine the shortest transportation path, since we must take into account enemy's threat. Therefore, this paper addresses the problem of finding the shortest transportation path considering both time and availability. To accomplish the objective of this study, values of k-shortest paths are computed using the algorithm for finding the k-shortest paths. Then availabilties of those paths are computed through simulation considering factors such as rates of suffering attack, damage and repair rates of the paths. An optimal path is selected using any one of the four decision rules that combine the value and availability of a path.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.90-96
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• 2011

Finding the critical path (or the longest path) on acyclic directed graphs, which is well-known as PERT/CPM, the ambiguity of each acr's length can be modeled as a range or an interval, in which the actual length of arc may realize. In this case, the min-max regret criterion, which is widely used in the decision making under uncertainty, can be applied to find the critical path minimizing the maximum regret in the worst case. Since the min-max regret critical path problem with the interval arc's lengths is known as NP-hard, this paper proposes a heuristic algorithm to diminish the maximum regret. Then the computational experiments shows the proposed algorithm contributes to the improvement of solution compared with the existing heuristic algorithms.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.1
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• pp.58-67
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• 1995

A path planning algorithm using a laser range finder are presented for real-tiem navigation of an autonomous guided vehicle. Considering that the laser range finder has the excellent resolution with respect to angular and distance measurements, a sophisticated local path planning algorithm is achieved by using the human's heuristic method. In the case of which the man knows not rhe path, but the goal direction, the man forwards to the goal direction, avoids obstacle if it appears, and selects the best pathway when there are multi-passable ways between objects. These heuristic principles are applied to the path decision of autonomous guided vehicle such as forward open, side open and no way. Also, the effectiveness of the established path planning algorithm is estimated by computer simulation in complex environment.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.931-939
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• 2003

This paper is aimed at proposing a new framework to predict decision performance, by Investigating decision maker's cognitive resonance. We assume that every decision maker has two kinds of schema­emotional schema and rational schema. Cognitive resonance is believed to have a close relationship with the two schemata and decision performance. In literature on decision performance there is no study' seeking relationship among the two schemata ana cognitive resonance. Therefore, our research purposes are twofold: (1) to provide a theoretical basis for the proposed framework describing the causal relationships among two schemata, cognitive resonance, and decision Performance, and (2) to empirically prove its validity applying to. Internet shopping Situation. Based on the questionnaires from 13S- respondents, we used a second order confirmatory factor analysis (CFA) to extract valid constructs, and structural equation model (SEM) to calculate path coefficients and prove the statistical validity of our proposed research model. Experimental results supported our research model with some further research issues.

• Korean Management Science Review
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• v.19 no.1
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• pp.55-66
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• 2002

Given a directed network, a designated arc, and lowers and upper bounds for the distance of each arc, the preprocessing shortest path problem Is a decision problem that decides whether there is some choice of distance vector such that the distance of each arc honors the given lower and upper bound restriction, and such that the designated arc is on some shortest path from a source node to a destination notre with respect to the chosen distance vector. The preprocessing shortest path problem has many real world applications such as communication and transportation network management and the problem is known to be NP-complete. In this paper, we develop an algorithm that solves the problem using the structural properties of shortest paths.

• Electronics and Telecommunications Trends
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• v.39 no.4
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• pp.10-20
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• 2024

Recent advancements in autonomous flight technologies for Unmanned Aerial Vehicles (UAVs) have greatly expanded their applicability for various tasks, including delivery, agriculture, and rescue. This article presents a comprehensive survey of path planning techniques in autonomous navigation and exploration that are tailored for UAVs. The robotics literature has studied path and motion planning, from basic obstacle avoidance to sophisticated algorithms capable of dynamic decision-making in challenging environments. In this article, we introduce popular path and motion planning approaches such as grid-based, sampling-based, and optimization-based planners. We further describe the contributions from the state-of-the-art in exploration planning for UAVs, which have been derived from these well-studied planners. Recent research, including the method we are developing, has improved performance in terms of efficiency and scalability for exploration tasks in challenging environments without human intervention. On the basis of these research and development trends, this article discusses future directions in UAV path planning technologies, illustrating the potential for UAVs to perform complex tasks with increased autonomy and efficiency.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3505-3516
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• 2021

During nuclear facility decommissioning, workers are continuously exposed to high-level radiation. Hence, adequate path planning is critical to protect workers from unnecessary radiation exposure. This work discusses recent development in radioactive path planning and the algorithms recommended for the task. Specifically, we review the conventional methods for nuclear decommissioning path planning, analyze the techniques utilized in developing algorithms, and enumerate the decision factors that should be considered to optimize path planning algorithms. As a major contribution, we present the quantitative performance comparison of different algorithms utilized in solving path planning problems in nuclear decommissioning and highlight their merits and drawbacks. Also, we discuss techniques and critical consideration necessary for efficient application of robots and robotic path planning algorithms in nuclear facility decommissioning. Moreover, we analyze the influence of obstacles and the environmental/radioactive source dynamics on algorithms' efficiency. Finally, we recommend future research focus and highlight critical improvements required for the existing approaches towards a safer and cost-effective nuclear-decommissioning project.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1085-1092
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• 2022

Travel distance is a parameter mainly used in the objective function of Construction Site Layout Planning (CSLP) automation models. To obtain travel distance, common approaches, such as linear distance, shortest-distance algorithm, visibility graph, and access road path, concentrate only on identifying the shortest path. However, humans do not necessarily follow one shortest path but can choose a safer and more comfortable path according to their situation within a reasonable range. Thus, paths generated by these approaches may be different from the actual paths of the workers, which may cause a decrease in the reliability of the optimized construction site layout. To solve this problem, this paper adopts reinforcement learning (RL) inspired by various concepts of cognitive science and behavioral psychology to generate a realistic path that mimics the decision-making and behavioral processes of wayfinding of workers on the construction site. To do so, in this paper, the collection of human wayfinding tendencies and the characteristics of the walking environment of construction sites are investigated and the importance of taking these into account in simulating the actual path of workers is emphasized. Furthermore, a simulation developed by mapping the identified tendencies to the reward design shows that the RL agent behaves like a real construction worker. Based on the research findings, some opportunities and challenges were proposed. This study contributes to simulating the potential path of workers based on deep RL, which can be utilized to calculate the travel distance of CSLP automation models, contributing to providing more reliable solutions.