Abstract
Adapting a real mobile robot in complex and changeable environments is one of the known challenging tasks in robotic researches. Complex environments are usually a combination of patterns, each of which requires a unique behavior from the robot to deal with. It is very difficult to develop a single network that can cope with such complex environments using the commonly known evolutionary algorithms. The network would be confused between adapting and readapting into each pattern and an optimal network would never occur. In this short paper, we proposed a simple structured adaptive controller with learning and memorizing ability that can cope with such complexity. The proposed controller works to simplify the complex environment into simple patterns that each of which could be independently trained. A memorizing mechanism is introduced to the controller to enhance the robot ability in tracking its own experiences and use it to cope with the upcoming events. Experiment results show that the proposed controller helps the stability of the robot performance in a complex environment
