• 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.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3010-3012
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• 2000

In this paper. we suggest a vector fitness strategy for obstacle avoidance of autonomous mobile robot with genetic algorithm. Ordinary genetic algorithms provide not such a viable solution for autonomous running in a variant environment. because of the difficulty in fitness evaluation in real time. We show that the suggested method is efficient for the problem of autonomous mobile robot. Its control function evolves to adapt the varying environment. The experiment is done using the real mobile robot 'Khepera' with which we use a tournament genetic algorithm model with the Vectored Fitness Genetic Strategy.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.61-67
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• 1999

There has been an ever increasing interest in mobile robot for home services. However, issues currently being investigated for path planning of the mobile robot is concentrated to solving the problem of finding the optimal path from the initial location to the final location under the given performance index. In this study, we newly present a sweeping algorithm for autonomous mobile robot to cover the whole closed area under the unknown environment. And we verify the validity the validity of the formalized algorithm by computer simulation with the changing environment conditions. In addition to this, we analyse the effect of real system implementation of the proposed algorithm to a experimental miniature mobile robit(Khepera).