The utility function method for behaviour selection in autonomous robots
In behaviour-based robotics (BBR), the artificial brain (or control system) of a robot is built from a repertoire of basic behaviours which are activated or deactivated through a process of behaviour selection that uses the state of the robot (and, possibly, its environment) as input [1-3]. Many behaviour-based systems are strongly reactive, i.e., there is a more or less direct connection between perception and action unlike the systems defined in classical artificial intelligence (AI) which are more deliberative, but typically operate quite slowly. In practice, it is common that the definition of a robotic brain involves a combination of the bottom-up approach defined in BBR and the topdown approach defined in classical AI . © 2010 Springer-Verlag London.