• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1319-1329
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• 2012

AGVs are more and more utilized nowadays and magnetic guided AGVs are most widely used because their system has low cost and high speed. But this type of AGVs requires high infrastructure building cost and has poor flexibility of navigation path layout changing. Thus it is hard to applying this type of AGVs to a small quantity batch production system or a cooperative production system with many AGVs. In this paper, we propose a vision based guideline interpretation technique that uses the cheap, easily installable and changeable color tapes (or paint) as a guideline. So a vision-based AGV with color tapes is effectively applicable to the production systems. For easy setting and changing of AGV navigation path, we suggest an automatic method for interpreting a complex guideline layout including multi-branches and joins of branches. We also suggest a trace direction decision method for stable navigation of AGVs. Through several real-time navigation tests with an industrial AGV installed with the suggested technique, we confirmed that the technique is practically and stably applicable to real industrial field.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.138-145
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• 2018

In the field of optimization, many studies have been performed on various types of Vehicle Routing Problem (VRP) for a long time. A variety of models have been derived to extend the basic VRP model, to consider multiple truck terminal, multiple pickup and delivery, and time windows characteristics. A lot of research has been performed to find better solutions in a reasonable time for these models with heuristic approaches. In this paper, by considering realtime traffic characteristics in Map Navigation environment, we proposed a method to manage realistic optimal path allocation for the logistics trucks and cargoes, which are dispersed, in order to realize the realistic cargo mixing allowance and time constraint enforcement which were required as the most important points for an online logistics brokerage service company. Then we developed a prototype system that can support above functionality together with delivery status monitoring on Map Navigation environment. First, through Map Navigation system, we derived information such as navigation-based travel time required for logistics allocation scheduling based on multiple terminal multiple pickup and delivery models with time constraints. Especially, the travel time can be actually obtained by using the Map Navigation system by reflecting the road situation and traffic. Second, we made a mathematical model for optimal path allocation using the derived information, and solved it using an optimization solver. Third, we constructed the prototype system to provide the proposed method together with realtime logistics monitoring by arranging the allocation results in the Map Navigation environment.

• Journal of the Korean Geographical Society
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• v.45 no.1
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• pp.144-164
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• 2010

This study aims to reveal path selection strategies and individual differences in a navigation task. Two experiments were presented that studied human route planning performance as well as the cognitive strategies and processes involved. For the outdoor task, university students were asked to select a route based on the instruction, i.e. to find the best route from the campus main gate to the Education Building for conference visitors by locating eight signposts. Results indicate (1) that locations of signposts were selected preferably at decision points where the traveler needs to make a choice and starting/ending points of the navigation task and (2) a variety of route planning strategies considering efficiency goal (e.g., the shortest path), environmental characteristics (e.g., fewest turns), and aesthetic purpose (e.g., most scenic) were used. It is notable that some participants took into account more than one path by locating one or two signposts on an alternative route while others preferred a linear route connecting signposts between the start point and the destination. Prior to the main experiment, the same participants were asked to complete the same task inside the classroom to investigate changes in strategies between two tasks. Participants often tend to place signposts at more regular intervals for the indoor navigation task than the same task conducted outside.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.832-842
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• 2020

The coordination control of multiple Underactuated Underwater Vehicles (UUVs) moving in three dimensional space is investigated in this paper. The coordinated path following control task is decomposed into two sub tasks, that is, path following control and coordination control. In the spatial curve path following control task, path following error dynamics is build in the Serret-Frenet coordinate frame. The virtual reference object can be chosen freely on the desired spatial path. Considering the speed of the UUV, the line-of-sight navigation is introduced to help the path following errors quickly converge to zero. In the coordination control sub task, the communication topology of multiple UUVs is described by the graph theory. The speed of each UUV is adjusted to achieve the coordination. The path following system and the coordination control system are viewed as the feedback connection system. Input-to-state stable of the coordinated path following system can be proved by small gain theorem. The simulation experiments can further demonstrate the good performance of the control method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1477-1491
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• 2017

Inspired by the multi-scale nature of hippocampal place cells, a biologically inspired model based on a multi-scale spatial representation for goal-directed navigation is proposed in order to achieve robotic spatial cognition and autonomous navigation. First, a map of the place cells is constructed in different scales, which is used for encoding the spatial environment. Then, the firing rate of the place cells in each layer is calculated by the Gaussian function as the input of the Q-learning process. The robot decides on its next direction for movement through several candidate actions according to the rules of action selection. After several training trials, the robot can accumulate experiential knowledge and thus learn an appropriate navigation policy to find its goal. The results in simulation show that, in contrast to the other two methods(G-Q, S-Q), the multi-scale model presented in this paper is not only in line with the multi-scale nature of place cells, but also has a faster learning potential to find the optimized path to the goal. Additionally, this method also has a good ability to complete the goal-directed navigation task in large space and in the environments with obstacles.

• 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 Korea Multimedia Society
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• v.20 no.4
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• pp.649-659
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• 2017

Typically, a smart car is equipped with access to the Internet and a wireless local area network. Moreover, a smart car is equipped with a global positioning system (GPS) based navigation system that presents a map to a user for recommending the shortest path to a desired destination. This paper presents the design and implementation of a real-time shortest path search system for directed and dynamic roads. Herein, we attempt to simulate real-world road environments, while considering changes in the ratio of directed roads and in road conditions, such as traffic accidents and congestions. Further, we analyze the effect of the ratio of directed roads and road conditions on the communication cost between the server and vehicles and the arrival times of vehicles. In this study, we compare and analyze distance-based shortest path algorithms and driving time-based shortest path algorithms while varying the number of vehicles to search for the shortest path, road conditions, and ratio of directed roads.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.782-791
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• 2005

In this paper, path planning and tracking problems are mentioned to guarantee efficient and safe navigation of autonomous mobile robots. We focus on the path planning and also deal with the path tracking and obstacle avoidance. We improved the conventional distance transform (DT) algorithm for the path planning. Using the improved DT algorithm, we obtain paths with shorter distances compared to the conventional DT algorithm. In the stage of the Path tracking, we employ the fuzzy logic controller to conduct the path tracking behavior and obstacle avoidance behavior. Through computer simulation studies, we show the effectiveness of the Nosed navigational algorithm for autonomous mobile robots.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.327-334
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• 2011

It is necessary that UGV(Unmanned Ground Vehicle) should generate a real-time travesability index map by analyzing raw terrain information to travel autonomously tough terrain which has various slope and roughness values. In this paper, we propose a local path planning method, $MA^*$(Modified $A^*$) algorithm, using DVGM (Directional Velocity Grid Map) for unmanned ground vehicle. We also present a path optimization algorithm and a path smoothing algorithm which regenerate a pre-planned local path by $MA^*$ algorithm into the reasonable local path considering the mobility of UGV. Field test is conducted with UGV in order to verify the performance of local path planning method using DVGM. The local path planned by $MA^*$ is compared with the result of $A^*$ to verify the safety and optimality of proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.295-299
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• 2005

In this paper, path planning and tracking problems are mentioned to guarantee efficient and safe navigation of autonomous mobile robots. We focus on the path planning and also deal with the path tracking and obstacle avoidance. We improved the conventional distance transform (DT) algorithm for the path planning. Using the improved DT algorithm, we obtain paths with shorter distances compared to the conventional DT algorithm. In the stage of the path tracking, we employ the fuzzy logic controller to conduct the path tracking behavior and obstacle avoidance behavior. Through computer simulation studies, we show the effectiveness of the proposed navigational algorithm for autonomous mobile robots.