Enhancing flexibility of vision‐based robots using an artificial neural network approach

摘要

Describes work based on the hypothesis that the use of artificial neural networks can imbue vision‐based robots with the ability to learn about their environment and hence enhance their competence and flexibility. The Neocognitron neural network provides the vision‐based robot with the capability of learning about its environment through training to recognize certain objects. The Neocognitron network is selected because of its ability to tolerate translational, rotational and scaling invariance in the input pattern of objects. Presents results which support the use of Neocognitron in enhancing the flexibility of vision‐based robots.