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Hierarchical intelligent control of a learning robot using a camera and system of artificial neural networks

Miljković Z.

Journal of Applied Computer Science

2000

Vol. 8, nr 2

79-97

This paper presents interaction of mechatronic subsystems in order to achieve an adaptive behavior of learning robots. A learning robot is able to deal flexibly with changes in its environment and to execute intelligent tasks. The control strategy for the learning robot is established by using a recognition system and machine learning. The recognition system that utilizes artificial intelligence techniques is used in order to test and verify the hypothesis that learning robots can achieve sensor-actuator co-ordination and team successfully. The hypothesis is tested and verified on the basis of visual information obtained from the camera and an artificial neural network system. For this purpose the experimental set of software packages Make it, ART-1 Simulator and BPNET, as well as the physical model of anthropomorphic mobile robot Don Kihot with four degrees of freedom, are realized.