• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.4
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• pp.622-628
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• 2012

This paper proposes an environment monitoring algorithm using a behavior-based multiple robot system. This paper handles an escort and a boundary-tracking especially. Unlike previous research works, the proposed environment monitoring system which is based on the behavior-based multiple robot control allows the system to employ the reusable code and general algorithm. Also, the proposed method can be applied to cheaper process with low performances. In the proposed method, escort and boundary-tracking missions are constructed by weighted sum of predefined basic behaviors after redefining the basic behaviors in previous works and introducing the novel basic behavior. Simulation results of the proposed method are included to demonstrate the practical application of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.297-305
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• 1999

Autonomous mobile robots are required to achieve multiple goals while responding quickly to the dynamic environments. An appropriate robot control architecture, which clearly and systematically defines the relationship among the inputs, the processing functions and the outputs, thus needs to be embedded in the robot controller. This paper proposes a kind of hybrid control architecture which combines the key features of the two well-known robot control architectures; hierarchical and behavioral- based. The overall control architecture consists of three layers, i.e. the highest planner, the middle plan executor, and the lowest monitor and behavior-based controller. In the planned situation, only one behavior module is chosen by the logical coordinator in the plan executor according to the way point bin. In the exceptional situation, the central controller in the plan executor issues an additional control command to reach the planned way point. Several simulations and experiments with autonomous mobile robot show that the proposed architecture enables the robot controller to achieve the multiple sequential goals even in dynamic and uncertain environments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.249-254
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• 2001

Abstract In this paper, we propose a method of cooperative control based on artifical intelligent system in distributed autonomous robotic system. In general, multi-agent behavior algorithm is simple and effective for small number of robots. And multi-robot behavior control is a simple reactive navigation strategy by combining repulsion from obstacles with attraction to a goal. However when the number of robot goes on increasing, this becomes difficult to be realized because multi-robot behavior algorithm provide on multiple constraints and goals in mobile robot navigation problems. As the solution of above problem, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for obstacle avoidance. Here, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for their direction to avoid obstacle. Our focus is on system of cooperative autonomous robots in environment with obstacle. For simulation, we divide experiment into two method. One method is motor schema-based formation control in previous and the other method is proposed by this paper. Simulation results are given in an obstacle environment and in an dynamic environment.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.192-200
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• 2012

In order for humans and robots to interact in daily life, robots need to understand human speech and link it to their actions. This paper proposes a hierarchical behavior model for robot action control using natural language commands. The model, which consists of episodes, primitive actions and atomic functions, uses a sentential cognitive system that includes multiple modules for perception, action, reasoning and memory. Human speech commands are translated to sentences with a natural language processor that are syntactically parsed. A semantic parsing procedure was applied to human speech by analyzing the verbs and phrases of the sentences and linking them to the cognitive information. The cognitive system performed according to the hierarchical behavior model, which consists of episodes, primitive actions and atomic functions, which are implemented in the system. In the experiments, a possible episode, "Water the pot," was tested and its feasibility was evaluated.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.435-441
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• 2013

A swarm robot system consists of with multiple mobile robots, each of which is called an agent. Each agent interacts with others and cooperates for a given task and a given environment. For the swarm robotic system, the loss of the entire work capability by malfunction or damage to a single robot is relatively small and replacement and repair of the robot is less costly. So, it is suitable to perform more complex tasks. The essential component for a swarm robotic system is an inter-robot collaboration strategy for teamwork. Recently, the swarm intelligence theory is applied to robotic system domain as a new framework of collective robotic system design. In this paper, FA (Firefly Algorithm) which is based on firefly's reaction to the lights of other fireflies and their social behavior is employed to optimize the group behavior of multiple robots. The main application of the firefly algorithm is performed on path planning of swarm mobile robots and its effectiveness is verified by simulations under various conditions.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.4
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• pp.160-166
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• 2002

Since conventional mobile robot control with one module has limitation to solve complex problems, there have been a variety of works on combining multiple modules for solving them. Recently, many researchers attempt to develop mobile robot controllers using artificial life techniques. In this paper, we develop a mobile robot controller using cellular automata based neural networks, where complex tasks are divided to simple sub-tasks and optimal neural structure of each sub-task is explored by genetic algorithm. Neural network modules are combined dynamically using the action selection mechanism, where basic behavior modules compete each other by inhibition and cooperation. Khepera mobile robot simulator is used to verify the proposed model. Experimental results show that complex behaviors emerge from the combination of low-level behavior modules.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.190-194
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• 1998

In this paper, we introduce the micro robot soccer playing system as a standard test bench for the study on the multiple agent system. Our method is based on following viewpoints. They are (1) any complex behavior such as cooperation among agents must be completed by sequential basic actions of concerned agents. (2) those basic actions can be well defined, but (3) how to organize those actions in current time point so as to result in a new stale beneficial to the end aim ought to be achieved by a kind of self-learning self-organization strategy.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1071-1076
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• 1990

This paper proposes a navigation strategy of multiple autonomous mobile robots with communication within a specified space. Assuming that each robot has complete detectability with finite range, simple navigation strategy is derived by introducing repulsive forces between robots and attractive force between a robot and its goal point analogous to those between electric charges. When a robot is close to its goal point, a pseudo-domain based on the distance between the closest point of the domain boundary and the goal point is proposed to enhance its convergence to the goal state. This paper concludes with the results of computer simulation studies on the dynamic behavior of multiple interacting robots with the proposed navigation strategy.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.92.4-92
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• 2002

In this paper, as an ideal test bed for studies on multi-agent system, the multiple micro robot soccer playing system is introduced at first. The construction of such experimental system has involved lots of kinds of challenges such as sensors fusing, robot designing, vision processing, motion controlling, and especially the cooperation planning of those robots. So in this paper we want to stress emphasis on how to evolve the system automatically based on the model of behavior-based learning in multi-agent domain. At first we present such model in common sense and then apply it to the realistic experimental system . At last we will give some results showing that the proposed approach is feasi...

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.12-15
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• 1988

A controller described in this paper is designed for implicit generalised minimum varience controller with variable time delays in which the weighting polynominals are calculated to reduce the output and control signals variances. This paper is based on the fact that the pole-assigment equation may have multiple solutions if the weighting polynominals are not of minimal order. It is shown that the larger order of the weighting polynominals increment the better is the stochastic behavior of the closed-loop system with variable time delays without changs in the deterministic behavior of the system. Based on this theory, the controller is applied to position control of a three-link manipulater with parameter uncertainty.