Teaching robots to coordinate its behaviours

Behaviour co-ordination is one of the major problems in behaviour-based robotics. This paper presents a teaching method for mobile robots to learn behaviour coordination. In this method, the sensory information is abstracted into a limited number of feature states that correspond to physical events in the interactive process between a robot and its environment. The continuous motor actions are abstracted into a limited number of behaviours. The goal of the behaviour co-ordination is to map the feature states into the behaviours in the light of environment rewards. The teaching process consists of an imitation stage and an autonomous learning stage. Both stages employ Q-learning algorithms to implement the mapping. The imitation stage serves as a preliminary stage for the teaching method. The learning result is used to bootstrap the autonomous learning stage. Experiments are conducted in the domain of soccer playing by Sony legged robots. Experiment results show that the robots can acquire behaviour coordination ability.