• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.9-17
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• 2021

In this paper, an autonomous multi-agent path planning using reinforcement learning for monitoring of infrastructures and resources in a computationally distributed system was proposed. Reinforcement-learning-based multi-agent exploratory system in a distributed node enable to evaluate a cumulative reward every action and to provide the optimized knowledge for next available action repeatedly by learning process according to a learning policy. Here, the proposed methods were presented by (a) approach of dynamics-based motion constraints multi-agent path-planning to reduce smaller agent steps toward the given destination(goal), where these agents are able to geographically explore on the environment with initial random-trials versus optimal-trials, (b) approach using agent sub-goal selection to provide more efficient agent exploration(path-planning) to reach the final destination(goal), and (c) approach of reinforcement learning schemes by using the proposed autonomous and asynchronous triggering of agent exploratory phases.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1989-1990
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• 2006

This paper presents an escaping route method in a trap situation (a case that the robot is trapped in a local minimum by the potential of obstacles). In this scheme, the APFs for path planning have a multiplicative and auditive configuration between APFs for goal destination and APFs for obstacle avoidance unlike conventional configuration where APFs for obstacle avoidance is added to APFs for goal destination. The virtual escaping route method is proposed to allow a robot to escape from a local minimum in trap situation where the total forces composed of repulsive forces by obstacles and attractive force by a goal are zero.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.542-552
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• 2018

Operators face challenges to plan alternative countermeasures when no procedure exists to address the current plant state. A model-based approach is desired to aid operators in acquiring plant resources and deriving response plans. Multilevel flow modeling (MFM) is a functional modeling methodology that can represent intentional knowledge about systems, which is essential in response planning. This article investigates the capabilities of MFM to plan alternatives. It is concluded that MFM has a knowledge capability to represent alternative means that are designed for given ends and a reasoning capability to identify alternative functions that can causally influence the goal achievement. The second capability can be applied to find originally unassociated means to achieve a goal. This is vital in a situation where all designed means have failed. A technique of procedure synthesis can be used to express identified alternatives as a series of operations. A case of station blackout occurring at the boiling water reactor is described. An MFM model of a boiling water reactor is built according to the analysis of goals and functions. The accident situations are defined by the model, and several alternative countermeasures in terms of operating procedures are generated to achieve the goal of core cooling.

• Journal of Korea Game Society
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• v.8 no.1
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• pp.79-90
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• 2008

This paper describes a motivation-based hierarchical behavior planning framework to allow autonomous agents to select adaptive actions in simulation game environments. The combined behavior planning system is formed by four levels of specification, which are motivation extraction, goal list generation, action list determination and optimization. Our model increases the complexity of virtual human behavior planning by adding motivation with sudden and cumulative attributes. The motivation selection by probability distribution allows NPC to make multiple decisions in certain situations in order to embody realistic virtual humans. Hierarchical goal tree enhances the effective reactivity. Optimizing for potential actions provides NPC with safe and satisfying actions to adapt to the virtual environment. A restaurant simulation game was used to elucidate the mechanism of the framework.

• The Journal of Korea Robotics Society
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• v.5 no.4
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• pp.302-308
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• 2010

A gradient method can provide a global optimal path in indoor environments. However, the optimal path can be often generated in narrow areas despite a sufficient wide area which lead to safe navigation. This paper presents a novel approach to path planning for safe navigation of a mobile robot. The proposed algorithm extracts empty regions using a ray-casting method and then generates temporary waypoints in wider regions in order to reach the goal fast and safely. The experimental results show that the proposed method can generate paths in the wide regions in most cases and the robot can reach the goal safely at high speeds.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.256-261
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• 2005

In this research, we propose a path-planning algorithm for an autonomous mobile robot using geographical information, under the condition that the robot moves in unknown environment. All image inputted by camera at every sampling time are analyzed and geographical elements are recognized, and the geographical information is embedded in environmental map. The geographical information was transformed into 1-dimensional evaluation value that expressed the difficulty of movement for the robot. The robot goes toward the goal searching for path that minimizes the evaluation value at every sampling time. Then, the path is updated by integrating the exploited information and the prediction on unexploited environment. We used a sensor fusion method for improving the mobile robot dead reckoning accuracy. The experiment results that confirm the effectiveness of the proposed algorithm on the robot's reaching the goal successfully using geographical information are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.131.4-131
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• 2001

A lot of path planning algorithms have been developed to find the collision-free path with minimum cost. But most of them require complicated computations. In this paper, a thinning method, which is one of the image processing schemes, was adopted to simplify the path planning procedure. In addition, critical points are used to find the shortest-distance path among all possible paths from the start to the goal point. Since the critical points contain the information on the neighboring paths, a new path can be quickly obtained on the map even when the start and goal points change. To investigate the validity of the proposed algorithm, various simulations have been performed for the environment where the obstacles with arbitrary shapes exist. It is shown that the optimal paths can be found with relative easiness.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.210-217
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• 2010

This paper presents integrated path planning and collision avoidance for an omni-directional mobile robot. In this scheme, the autonomous mobile robot finds the shortest path by the descendent gradient of a navigation function to reach a goal. In doing so, the robot based on the proposed approach attempts to overcome some of the typical problems that may pose to the conventional robot navigation. In particular, this paper presents a set of analysis for an omni-directional mobile robot to avoid trapped situations for two representative scenarios: 1) Ushaped deep narrow obstacle and 2) narrow passage problem between two obstacles. The proposed navigation scheme eliminates the nonfeasible area for the two cases by the help of the descendent gradient of the navigation function and the characteristics of an omni-directional mobile robot. The simulation results show that the proposed navigation scheme can effectively construct a path-planning system in the capability of reaching a goal and avoiding obstacles despite possible trapped situations under uncertain world knowledge.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.339-346
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• 2005

Artificial potential field (APF) is a widely used method for local path planning of autonomous mobile robot. So far, many different types of APF have been implemented. Once the artificial potential functions are selected, how to choose appropriate parameters of the functions is also an important work. In this paper, a detailed analysis is given on how to choose proper parameters of artificial functions to eliminate free path local minima and avoid collision between robots and obstacles. Two kinds of potential functions: Gaussian type and Quadratic type of potential functions are used to solve the above local minima problem respectively. To avoid local minima occurred in realistic situations such as 1) a case that the potential of the goal is affected excessively by potential of the obstacle, 2) a case that the potential of the obstacle is affected excessively by potential of the goal, the design guidelines for selecting appropriate parameters of potential functions are proposed.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.17-32
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• 2013

Reckless development policy, which has continued during the past several decades, caused landscape damage. In order to solve this problem, it is very urgent to conserve the habitat and to establish systematic database. Recently, various researches related to landscape damage have been conducted actively and the necessity of landscape ecological planning based on the biotop mapping has been issued as one of the solutions. Therefore, the purpose of this study is to select the study area, which is located in Guji-meon, Dalseong-gun, Daegu and will be formed into Daegu Science Park, and then to develop and apply the landscape ecological planning model based on biotop mapping in district unit. The results are as follows. Fist of all, according to the results of biotop classification with field survey and literature review, total 13 biotop and total 63 biotop types were classified. According to the first evaluation with B-VAT, total 19 biotop types were classified I grade including natural river with abundant plants(BA) and so on. While V grade, which has lowest value, was classified 16 biotop types including vegetable garden adjacent to river(BC). Also the second evaluation, we analyzed total 30 areas such as 1a, 1b grades, which had special meaning for the conservation of species and biotop. Next, 2a, 2b, 2c grades were analyzed total 82 areas. Secondly, in the compliance with Ecological landscape planning, we divided landscape planning model into two parts such as setting of improvement goal and detailed implement plan. For instance, setting of improvement goal, we classified 9 parts such as conservation region and parts of detailed implement plan, we classified total 28 planning indicators with 4 view such as the region which should be special protected from nature and landscape. Lastly, with the developed landscape model we applied to research areas, made maps, and differentiate proposals in each region. Specially, the final master plan was made to help understand the contents of detailed landscape planning. This study will be a useful data, which can solve the landscape damage problem systematically and control it landscape-friendly with biotop classification, evaluation, landscape ecological planning model, and application method which we developed.