Abstract
In the recent years, neural networks or other learing networks are frequently used in the field of robotics. However, the needed conditions of the learning system are not fulfilled enough in autonomous robot, because the variety of the needed conditions let it difficult to accomplish. So, integration of the functions is inevitable to create an effective learning system in autonomous robot. In traditional methods, it was difficult to accomplish “autonomous exploration of the effective output”, “simple external parameters”, and “low calculation cost” together in a learning system. Thus, we proposed a new learning method self-organizing network elements (SONE) against this problem. All of these conditions are fulfilled by SONE, however there is a need to enhance the ability against noises. Therefore, we propose a technique to restrain noises in SONE. In our experiments, more resistance against noises was confirmed with this technique. Also in a robot simulation, the performance of the robot was improved by this novel method.
