• Journal of Power System Engineering
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• v.16 no.1
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• pp.84-90
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• 2012

In unmanned vehicles' navigation, the shapes of obstacles are generally irregular and complex. The motion of vehicles based on the range sensor system such as ultrasonic sensors or laser sensors can be unstable due to the irregular shape of the obstacles. In this case, to generate stable trajectory of unmanned vehicles equipped with range sensors, we need an approach that can simplify an obstacle's irregular shape information. In this paper, we propose the trajectory generation algorithm that an vehicle can stably navigate in the environments where irregular shaped obstacles are scattered. The proposed method is verified through the analysis of vehicle's trail and direction data acquired by simulations and implementations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.10
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• pp.996-1002
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• 2008

This paper presents the development of a real-time algorithm for collision detection, collision avoidance and guidance to way-point. Three-dimensional point-mass aircraft models are used. For collision detection, time of closest point of approach(CPA) and distance at CPA are compared to threshold values. For collision avoidance, optimal acceleration input which maximizes the terminal relative distance is calculated based on optimal control theory. For guidance to way-point, proportional navigation guidance, the well-known method, is used. Two scenarios of encounter situation are illustrated to validate performance of proposed algorithm.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.16-23
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• 2011

In this paper, nonlinear model predictive control (NMPC) is addressed to develop formation guidance for multiple unmanned aerial vehicles. An NMPC algorithm predicts the behavior of a system over a receding time horizon, and the NMPC generates the optimal control commands for the horizon. The first input command is, then, applied to the system and this procedure repeats at each time step. The input constraint and state constraint for formation flight and inter-collision avoidance are considered in the proposed NMPC framework. The performance of NMPC for formation guidance critically degrades when there exists a communication failure. In order to address this problem, the modified optimal guidance law using only line-of-sight, relative distance, and own motion information is presented. If this information can be measured or estimated, the proposed formation guidance is sustainable with the communication failure. The performance of this approach is validated by numerical simulations.

• Korean Journal of Psychosomatic Medicine
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• v.4 no.1
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• pp.124-137
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• 1996

As the society becomes more industrialized and modernized, we have more chances to experience a serious traumatic event. Post-traumatic stress disorder (PTSD) has 3 major categories of symptoms such as memory disturbance, hyperarousal and avoidance or numbness. I reviewed the psychobiological evidences in 3 main categories of symptoms and the biological treatment after a brief review of the epidemiology, psychosocial etiology and diagnosis of PTSD. The memory disturbance of PTSD might be developed by the potentiation of the memory pathway mediated by norepinephrine. PTSD induces HPA axis abnormality, it might also develop hippocampal dysfunction, which might contribute to the memory disturbance. The kindling effect develops desensitization, which might develop reexperiencing of the traumatic events and hyperarousal state. Chronic aroused state of locus ceruleus with resultant chronic maladaptive state of norepinephrine system, might develop hyperarousal state. Social avoidance and physical numbing state in PTSD might be caused by serotnin or opiate system. Stress induced analgesia might be developed by opiate reliesed against the acute stress. The biologic research results would help the selective treatment of PTSD.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.94-99
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• 1993

In this paper, the method for navigation and obstacle avoidance of an autonomous mobile robot is proposed. It is based on the fuzzy inference system which enables to deal with imprecise and uncertain information, and on the neural network which enables to learn input and output pattern data obtained from ultrasonic sensors. For autonomous navigation, the wall-following navigation utilizing input and output data by an expert's control action is constructed. An approach by the neural network is developed for the obstacle avoidance because of the redundant input data. For an autonomous navigation, the fuzzy control and the control of the neural network are integrated and its feasibility is demonstrated by means of experiment.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.304-306
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• 2001

This paper presents the obstacle avoidance of a biped walking robot using GA-Fuzzy algorithm. In the case of our previous studies the surface has been assumed to be flat. For the case of the environment with obstacles, however, the walking robot might be unnatural. Thus, we considered the surface contained obstacles that the robot can pass through. We propose the optimal leg trajectory data-base by using genetic algorithm and optimal leg trajectory movement about obstacles that exist in front of the robot using fuzzy approach. It is shown that the robot can move more naturally on the surface that contains obstacles.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.164.1-164
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• 2001

Q-learning is a recent reinforcement learning algorithm that does not need a modeling of environment and it is a suitable approach to learn behaviors for autonomous agents. But when it is applied to multi-agent learning with many I/O states, it is usually too complex and slow. To overcome this problem in the multi-agent learning system, we propose the successive Q-learning algorithm. Successive Q-learning algorithm divides state-action pairs, which agents can have, into several Q-functions, so it can reduce complexity and calculation amounts. This algorithm is suitable for multi-agent learning in a dynamically changing environment. The proposed successive Q-learning algorithm is applied to the prey-predator problem with the one-prey and two-predators, and its effectiveness is verified from the efficient avoidance ability of the prey agent.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.134.6-134
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• 2001

The purpose of navigation algorithm is to reach a given target point without collision with obstacles while an autonomous mobile robot is navigating. To achieve a safe navigation, this paper presents an effective navigation algorithm for the autonomous mobile robot equipped with ultrasonic sensors in unknown environments. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The decision maker using fuzzy inference systems weights the steering angles selected ...

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1040-1045
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• 1991

An approach to time-varying obstacle avoidance problem is pursued. The mathematical formulation of the problem is given in Cartesian space and in joint space. To deal with the time-varying obstacles, view-time is introduced. A view-time is the time interval viewing the time-varying obstacles to model equivalent stationary obstacles. For the analysis of the properties of the view-time, avoidability measure is defined as a measure of easiness for a robot to avoid obstacles. Based on the properties, a motion planning strategy to avoid time-varying obstacles is derived. An application of the strategy to the collision-free motion planning of two SCARA robots and the simulation on the application are given.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2678-2686
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• 2002

A novel approach is developed for avoidance of obstacles in unknown environment. This paper proposes a new way of intelligent autonomous wheelchairs for the handicapped to move safely and comfortably. It is the objective of this paper to develop delayed time fuzzy control algorithms to deal with various obstacles. This new algorithm gives the benefit of the collision free movement in real time and optimal path to the moving target. The computer simulations and the experiments are demonstrated to the effect of the suggested control method.