• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.120-125
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• 2013

This paper proposes a goal oriented action planning method that plans the behaviors of computer generated forces and a replanning method that replans new actions when the situations are changed in war game. This new method provides good expression because it is flexible and can do more realized description unlike the conventional finite state machines. As a result, proposed method has an advantage that it can describe the behaviors of computer generated forces as those of real soldier. However, since it is not deterministic it has some difficulties in analysing the decision processing of behaviors and making the computer generated forces do some specific actions. We employed combat plane models of air forces in order to verify the feasibility of our method. Finally, we could find that our method produced very similar behaviors to those of a real soldier. This paper describes our planning method, experimental results, and future works.

• Journal of the Korea Society for Simulation
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• v.20 no.1
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• pp.69-77
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• 2011

Modeling and Simulation(M&S) technology gets an attention from various parts such as industry and military. Especially, military uses the technology to cope with a different situation from the one in the Cold War and maximize the effect of training against the cost in the new environment. In order for the training based on M&S technology to be effective, the situations of a battlefield and a combat must be more realistically simulated. For this, a technique development on Computer-Generated Forces(CGF) which represents a unit's simulation logic and a human's simulated behaviors is focused. The CGF simulating a human's behaviors can be used in representing an enemy force, experimenting behaviors in a future war, and developing a new combat idea. This paper describes a methodology to accomplish Computer-Generated Forces' autonomous intelligence. It explains the process of applying a task behavior list based on the METT+T element onto CGFs. On the other hand, in the domain knowledge of military field manual, fuzzy facts such as "fast" and "sufficient" whose real values should be decided by domain experts can be easily found. In order to efficiently implement military simulation logics involved with such subjectivity, using a fuzzy inference methodology can be effective. In this study, a fuzzy inference methodology is also applied.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.132-139
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• 2005

The driving position of head restraints and the relative risk of neck injury were studied in the computer simulation. MADYMO human model with the detail neck model was used to define the magnitude and direction of internal forces acting on the cervical spine during rear-end impact and to determine the effect of the initial position of the occupant's head with respect to the head restraints. Maximum reaction forces were generated during the head contact to the restraint and relatively large forces were generated at each spinal components in lower cervical spine in proportion to backset and height distance increasement.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.4
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• pp.390-400
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• 2022

Military deception is an action executed to deliberately mislead enemy's decision by deceiving friendly forces intention. In the lessons learned from war history, deception appears to be a critical factor in the battlefield for successful operations. As training using war-game simulation is growing more important, it is become necessary to implement military deception in war-game model. However, there is no logics or rules proven to be effective for CGF(Computer Generated Forces) to conduct deception behavior automatically. In this study, we investigate methodologies for CGF to learn and conduct military deception using Reinforcement Learning. The key idea of the research is to define a new criterion called a "deception index" which defines how agent learn the action of deception considering both their own combat objectives and deception objectives. We choose Korea Marine Corps Amphibious Demonstrations to show applicability of our methods. The study has an unique contribution as the first research that describes method of implementing deception behavior.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.888-893
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• 2008

In This paper proposes the control algorithm for quadruped robots on irregularly sloped uneven surface. Body balance is important in stable running locomotion. Since the body balance is determined by the forces applied at the feet during touchdown phase, the ground reaction force is controlled for stable running. To control the forces at each foot, the desired force is generated. The generated desired force is compared with actual contact force, then, the difference between them modifies the foot trajectory. The desired force is generated by combination of the rate change of the angular and linear momentum at flight. Then the rate change of momentum determines each force distribution. The distribution of the force is carried out by fuzzy logic. The computer simulation is carried out with the commercial software RecurDyn$^{(R)}$. Dynamic model simulation program show that the stable running on the irregularly sloped uneven surface are accomplished by the proposed method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.135-138
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• 2005

Robotic devices have been widely used in many medical applications due to their accuracy and programming ability. One of the applications is a virtual reality medical simulator, which trains medical personnel in a computer generated environment. In this paper, we are going to present an application, an epidural anesthesia trainer. Because performing epidural injections is a delicate task, it demands a high level of skill and precision from the physician. This trainer uses a robotic device and computer controlled solenoid valve to recreate interaction forces between the needle and the various layers of tissues around the spinal cord. The robotic device is responsible for generation of interaction forces in real time and can be used to be haptic guidance that allows the user to follow a previous recorded expert procedure and feel the encountered forces.

• Journal of Power System Engineering
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• v.13 no.2
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• pp.71-82
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• 2009

This paper presents a real-time haptic rendering method for a realistic force feedback in a remote environment with varying communication time-delay. The remote environment is assumed as a virtual environment based on a computer graphics, for example, on-line shopping mall, internet game and cyber-education. The properties of a virtual object such as stiffness and viscosity are assumed to be unknown because they are changed according to the contact position and/or a penetrated depth into the object. The DARMAX model based output estimator is proposed to trace the correct impedance of the virtual object in real-time. The output estimator is developed on the input-output relationship. It can trace the varying impedance in real-time by virtue of P-matrix resetting algorithm. And the estimator can trace the correct impedance by using a white noise that prevents the biased input-output information. Realistic output forces are generated in real-time, by using the inputs and the estimated impedance, even though the communication time delay and the impedance of the virtual object are unknown and changed. The generated forces trace the analytical forces computed from the virtual model of the remote environment. Performance is demonstrated by experiments with a 1-dof haptic device and a spring-damper-based virtual model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.42-48
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• 2011

Agent acts for specification purpose, which is common element of CGF (Computer Generated Forces). When basic agent acts as planned, the advanced intelligence agent can do more than this. It can follow predefined actions along appointed script to achieve purpose or lay another plans when it is difficult to achieve. In other words, it can amend plan again or make new plan in order to achieve goals. When plan fails, agent amends oneself, possibly decreases target level to achieve easily. In doing so, the agent calculates a quantitative value for changing plans in realtime, and choose appropriate alternative plans when the threshold value reaches an limit. In this paper, we propose an military system in which the planned action can be modified according to the level of achievement and alternative plans can be generated accordingly.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.11-18
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• 2011

This paper proposes a novel planning method for computer generated forces (CGFs) in war games that plans the behaviors of CGFs according to a given mission and situations. CGFs which are received their missions first plan their tasks for accomplishing the mission and then plan their behaviors for accomplishing each task. After that, they execute their planned behaviors considering the conditions of environments (in other words situations). The tasks and behaviors are hierarchically composed and include start conditions for beginning those and termination conditions for stopping those. CGFs first check whether the start condition of the planned behavior for accomplishing a task is satisfied or not in some degree and perform the behavior if satisfied continuously until the termination condition of the behavior will be met. If the termination condition is satisfied, then they check the start condition of the next planned behavior. This process will be repeated for accomplishing the mission. If the situations of CGFs are different by changing the environments from those of planning time, it may cause the start condition of the planned behavior to be dissatisfied. In this case, CGFs can decide a new behavior using fuzzy rule base. We realized our planning system and tested CGFs with a scenario. Experimental results showed that our system worked well and actively coped with situation changes. It will be possible to make CGFs that can do more autonomous behaviors if we continually develop our method.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.333-335
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• 2012

가상군의 자율행위 모델링은 전장모의모델링 시스템의 성능을 결정하는 주요한 요소이다. 불확실한 상황을 확률적으로 고려하여 최적의 의사결정을 가능하게 하는 POMDP (partially observable Markov decision process) 모델은 가상군의 자율행위 모델링에 있어서 매우 자연스러운 프레임워크이다. 그러나 POMDP 모델의 높은 계산복잡도로 인한 최적 행동정책 계산의 어려움은 POMDP 모델을 이용한 가상 군의 자율행위 모델링을 저해하는 요소이다. 본 논문에서는 대규모 가상군의 자율행위 모델링을 위해 factored POMDP 모델을 이용한다. 그리고 "Hasty Defense" 사례연구를 통해 그 효과를 확인한다.