• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.259-262
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• 2003

In this paper, we studied the path determination algorithm of the guidance robot for the visually impaired. Using the guidance robot for the visually impaired, the visually impaired can go to the destination where they want without other's heir. The navigation path of the guidance robot for the visually impaired must be the optimal path not only the shortest but also the most safe, which is different from a shortest path for common people. GPS and electronic map are used for the location information of the visually impaired. We corrected the error by converting the coordinates of location information from GPS, which includes maximum several tens of meters error, to the coordinates of electronic map. Information such as simple path and direction to the destination is not enough because it may be different between a going path from the start to the destination and a coming path from the destination to the start as around environment. So, we added information which can be dangerous for the visually impaired such as driveway, sidewalk without braille blocks, crosswalk, stairs and overpass, each has weight value as dangerous degree, when matching the GPS information to the electronic map, enough large as 1:5,000 scale.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.117-123
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• 2023

There are casualties due to inundation and flooding due to intensive typhoons or heavy rains in summer. Due to such damage, the biggest disaster is flood, and in order to reduce human damage, this paper proposes a shortest distance algorithm-based pedestrian path search study using Map API. This system selects Map API through comparative analysis and provides the shortest route. The route explored is in JSON format and the data of the shelter is stored in the database. The route search system designed and implemented based on this data locates pedestrians and provides evacuation routes in case of flash floods. In addition, if the route cannot be entered while moving to the evacuation route, the current location of the pedestrian is identified, the route is re-searched, and a new route is provided. Therefore, it is believed that the pedestrian route search system proposed in this paper will prevent negligent accidents.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.219-221
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• 2022

In recent summer, as it is concentrated, even in mountainous areas, flooding and flooding cause casualties in pedestrian evacuation situations. To compensate for this, a system that detects the occurrence of flooding and allows pedestrians to evacuate safely is required. Therefore, in this paper, we propose a research on pedestrian path search based on the shortest distance algorithm using Map API. The pedestrian route search system outputs a map using the T Map API, selects nearby buildings as shelters, and stores data. A shelter close to the pedestrian's current location is selected, and the shortest route is output and the distance and time are provided. If there is a problem with the current route during evacuation, another shelter route is provided from the current location. Therefore, it is thought that the pedestrian route search evacuation system proposed in this paper will prevent accidents during evacuation.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.42-48
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• 1999

Consider the situation that informations necessary to solve a certain problem are distributed among processors on a network. It is called a distributed algorithm that in this situation each processor exchanges the message with adjacent processors to solve the problems. This paper proposes a distributed algorithm to solve the problem that constructs the weighted shortest path tree in an asynchronous network system. In general, a distributed algorithm is estimated by the number of messages(message complexity of the distributed algorithm proposed in this paper are O(n53) and O(nln) respectively. where n is the number of processors on the network.

• Journal of the Korea Society of Computer and Information
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• v.21 no.7
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• pp.47-52
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• 2016

This paper introduces an algorithm to construct an Eulerian cycle for Chinese postman problem. The Eulerian cycle is formed only when all vertices in the graph have an even degree. Among available algorithms to the Eulerian cycle problem, Edmonds-Johnson's stands out as the most efficient of its kind. This algorithm constructs a complete graph composed of shortest path between odd-degree vertices and derives the Eulerian cycle through minimum-weight complete matching method, thus running in $O({\mid}V{\mid}^3)$. On the contrary, the algorithm proposed in this paper selects minimum weight edge from edges incidental to each vertex and derives the minimum spanning tree (MST) so as to finally obtain the shortest-path edge of odd-degree vertices. The algorithm not only runs in simple linear time complexity $O({\mid}V{\mid}log{\mid}V{\mid})$ but also obtains the optimal Eulerian cycle, as the implementation results on 4 different graphs concur.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2417-2419
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• 2001

A path planning is one of the main subjects in a mobile robot. It is divided into two parts. One is a global path planning and another is a local path planning. This paper, using the formal two methods, presents that the mobile robot moves to multi-targets with avoiding unknown obstacles. For the shortest time and the lowest cost, the mobile robot has to find a optimal path between targets. To find a optimal global path, we used GA(Genetic Algorithm) that has advantage of optimization. After finding the global path, the mobile robot has to move toward targets without a collision. FLC(Fuzzy Logic Controller) is used for local path planning. FLC decides where and how faster the mobile robot moves. The validity of the study that searches the shortest global path using GA in multi targets and moves to targets without a collision using FLC, is verified by simulations.

• IE interfaces
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• v.25 no.3
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• pp.365-375
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• 2012

An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky or uninhabitable for humans. UAVs are currently employed in many military missions and a number of civilian applications. For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a $A^*PS$_PGA (A-star with Post Smoothing_Parallel Genetic Algorithm) for Multiple UAVs's path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and MTSP (Multiple Traveling Salesman Problem). After transforming MRPP into Shortest Path Problem (SPP),$A^*PS$_PGA applies a path planning for multiple UAVs.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.77-78
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• 2008

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm and the particle swarm optimization. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the particle swarm optimization method. At first, we produce paths of a mobile robot in the static environment. And then, we find midpoints of each path using the Maklink graph. Finally, the hybrid algorithm is adopted to get a shortest path. We prove the performance of the proposed algorithm is better than that of the path planning algorithm using the ant colony optimization only through simulation.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.311-312
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• 2007

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the Maklink graph method. At first, we produce the path of a mobile robot a the static environment. And then we find midpoints of each path using the Maklink graph. Finally the ant colony optimization algorithm is adopted to get a shortest path. In this paper, we prove the performance of the proposed algorithm is better than that of the Dijkstra algorithm through simulation.