• Korean Journal of Computational Design and Engineering
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• v.15 no.4
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• pp.306-313
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• 2010

In this paper, an acceleration based passenger evacuation simulation is performed. In order to describe a passenger‘s behavior in an evacuation situation, a passenger is modeled as a rigid body which translates in the horizontal plane and rotates along the vertical axis. The position and rotation angle of a passenger are calculated by solving the dynamic equations of motions at each time step. The destination force, the contact force, and the group force are considered as external forces and the moments due to each force are also considered. With the passenger model proposed in this paper, the test problems in International Maritime Organization, Maritime Safety Committee/Circulation 1238(IMO MSC/Circ.1238) are implemented and the effects of passenger rotation on the evacuation time are confirmed.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.105-114
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• 2011

The roadmap-based planning is a path planning method which is used widely for a goal-directed movement in Robotics and has been applied to the world of computer animation such as computer games. However it is unnatural for computer characters to follow the path planned by the roadmap method as it is performed in Robotics. Flocking which is used for realistic and natural movements in computer animation enables character's movement by using a few simple rules without planning unlike the roadmap method. However it is impossible to achieve a goal-directed movement with flocking only because it does not keep states. In this paper we propose a simulation method which combines planning based on the road map with reactive actions for natural movements along the path planned. We define and implement steering behaviors for a leader which are needed to follow the trajectory naturally by analysing characteristics of roadmap-based paths and for the rest of members which follow the leader in various manners by detecting obstacles. The simulations are performed and demonstrated by using the implemented steering behaviors on every possible combination of roadmap-based path planning methods and models of configuration spaces. We also show that the detection of obstacle-collisions can be done effectively because paths are planned in the configuration space in which a moving object is reduced to a point.

• The Journal of the Korea institute of electronic communication sciences
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• v.2 no.3
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• pp.157-162
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• 2007

The goal of researching a proper crowd animation is to design system that is satisfied with the reality of scenes, performance of system, and interaction with users to show the crowd vividly and effectively in virtual underwater world. In this paper, we smartly expressed the behavior patterns for flocks of fish in virtual underwater and we made up for the weak points in spending time and cost to produce crowd animation. We compared with the number of mesh, the number of fish, the number of frame, elapsed time, and resolution and analyzes them with the fish behavior simulating system. We developed a virtual underwater simulator using this system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.4
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• pp.266-273
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• 2019

The efficiency and effectiveness of mission performance can be greatly changed according to the operating conditions such as the number of manned aircraft, flight altitude, and so on, in performing search and reconnaissance missions using a large number of small reconnaissance unmanned aerial vehicles. However, it is not easy to determine which operating conditions are most reasonable. Therefore, in this study, we developed an unmanned airplane flight simulation that can detect and identify the target while avoiding collision according to autonomous flight, suggesting a way to derive operating conditions when operating a large number of unmanned aerial vehicles.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.8
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• pp.573-580
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• 2020

One of challengeable problems of multi-agent systems is a positioning control. Augmented Cucker-Smale model is using for controlling position and velocity of the multi-agent system. The original model applies same coefficients to all agents in same group, so that does not consider characteristic of each agent. To enhance performance of the original model, this paper transforms original coefficients to Mahalanobis distance coefficients that reflects an initial distribution of multi-agent systems and applies statistical degrees of freedom. This paper not only confirms tendency of enhanced performance of the suggested model by using monte-carlo simulation, but also additionally compares trajectory of the original model with the suggested model to confirm coefficients of Mahalanobis distance performing correctly.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.117-129
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• 2024

This paper introduces collective navigation through a narrow gap using a curriculum-based deep reinforcement learning algorithm for a swarm of unmanned aerial vehicles (UAVs). Collective navigation in complex environments is essential for various applications such as search and rescue, environment monitoring and military tasks operations. Conventional methods, which are easily interpretable from an engineering perspective, divide the navigation tasks into mapping, planning, and control; however, they struggle with increased latency and unmodeled environmental factors. Recently, learning-based methods have addressed these problems by employing the end-to-end framework with neural networks. Nonetheless, most existing learning-based approaches face challenges in complex scenarios particularly for navigating through a narrow gap or when a leader or informed UAV is unavailable. Our approach uses the information of a certain number of nearest neighboring UAVs and incorporates a task-specific curriculum to reduce learning time and train a robust model. The effectiveness of the proposed algorithm is verified through an ablation study and quantitative metrics. Simulation results demonstrate that our approach outperforms existing methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.355-362
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• 2009

In this paper, we present a framework for managing group behaviors in multi-agent swarm systems. The framework explores the benefits by dynamic associations with the proposed artificial potential functions to realize complex swarming behaviors. A key development is the introduction of a set of flocking by dynamic association (DA) algorithms that effectively deal with a host of swarming issues such as cooperation for fast migration to a target, flexible and agile formation, and inter-agent collision avoidance. In particular, the DA algorithms employ a so-called systematic singular association (SSA) rule for fast migration to a target and compact formation through inter-agent interaction. The resulting algorithms enjoy two important interrelated benefits. First, the SSA rule greatly reduces time-consuming for migration and satisfies low possibility that agents may be lost. Secondly, the SSA is advantageous for practical implementations, since it considers for agents even the case that a target is blocked by obstacles. Extensive simulation presents to illustrate the viability and effectiveness of the proposed framework.

• Journal of Korea Game Society
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• v.13 no.6
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• pp.27-34
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• 2013

This paper analyzes the behaviour of a prey to avoid the pursuit of a predator at predator-prey relationship to be appeared in the collective behavior of animals. One of the methods to avoid the pursuit of a predator is to rotate quickly when a predator arrives near to it. At that moment, a critical distance and a rotating angular are very important for the prey in order to survive from the pursuit, where the critical distance is the distance between the predator and the prey just before rotation. In order to analyze the critical distance and the rotating angular, this paper introduces the energy for a predator which it has at starting point of the chase and consumes during the chase. Through simulations, we can know that the rotating angle for a prey to survive from the pursuit is increased when the critical distance is shorter and when the ratio of predator's mass and prey's mass is also decreased. The results of simulations are the similar phenomenon in nature and therefore it means that the method to analyze in this paper is correct.

• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.37-43
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• 2010

In field, one can observe without difficulties that two flocks are intersected or combined with each other. For example, a fish flock in a stream separates into two part by obstacles (e.g. stone) and rejoins behind the obstacles. The dynamics of two flocks guided by their leader were studied in the situation where the flocks cross each other with a crossing angle, ${\theta}$, between their moving directions. Each leader is unaffected by its flock members whereas each member is influenced by its leader and other members. To understand the dynamics, I investigated the order parameter, ${\phi}$, defined by the absolute value of the average unit velocity of the flocks' members. When the two flocks were encountered, the first peak in ${\phi}$ was appeared due to the breaking of the flocks' momentum balance. When the flocks began to separate, the second peak in ${\phi}$ was observed. Subsequently, erratic peaks were emerged by some individuals that were delayed to rejoin their flock. The amplitude of the two peaks, $d_1$ (first) and $d_2$ (second), were measured. Interestingly, they exhibited a synchronized behavior for different ${\theta}$. This simulation model can be a useful tool to explore animal behavior and to develop multi-agent robot systems.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.122-131
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• 2010

This paper introduces the concept of a virtual ecosystem and reports the following three mathematical approaches that could be widely used to construct such an ecosystem, along with examples: (1) a molecular dynamics simulation approach for animal flocking behavior, (2) a stochastic lattice model approach for termite colony behavior, and (3) a rule-based cellular automata approach for biofilm growth. The ecosystem considered in this study consists of artificial organisms and their environment. Each organism in the ecosystem is an agent that interacts autonomously with the dynamic environment, including the other organisms within it. The three types of model were successful to account for each corresponding ecosystem. In order to accurately mimic a natural ecosystem, a virtual ecosystem needs to take many ecological variables into account. However, doing so is likely to introduce excess complexity and nonlinearity in the analysis of the virtual ecosystem's dynamics. Nonetheless, the development of a virtual ecosystem is important, because it can provide possible explanations for various phenomena such as environmental disturbances and disasters, and can also give insights into ecological functions from an individual to a community level from a synthetic viewpoint. As an example of how lower and higher levels in an ecosystem can be connected, this paper also briefly discusses the application of the second model to the simulation of a termite ecosystem and the influence of climate change on the termite ecosystem.