Cognitive Robot Cooperation

In recent years, cognitive robots have become an attractive research area of Artificial Intelligent (AI). High-order beliefs for cognitive robots regard the robots' thought about their users' intention and preference. The existing approaches to the development of such beliefs through machine learning rely on particular social cues or specifically defined award functions. Therefore, their applications can be limited. This paper presents an active robot learning based approach to facilitate the robots to develop the beliefs by actively collecting/discovering evidence it needs. The emphasis is on active learning, but not teaching. Hence social cues and award functions are not necessary. This paper introduces fuzzy logic theory to the designing of cognitive robot. A robot arm with two fuzzy logic controllers cooperates with another traditional robot arm. They lift an object jointly and keep it level.The simulation process is on computer and uses MATLAB environment. The two robot arm hold each side of a stick and one robot arm is moving according to a fixed trajectory and the other try to cooperate with it actively. The robot arm acquires information from a tilt sensor. The experimental results show that under the framework a robot is able to discover the evidence it needs to confirm its user's intention.