Behaviour Based Control with Fuzzy Automaton in Vehicle Navigation

From the viewpoint of Behaviour based Control many control tasks can be divided into separate behaviour components. By defining the relevant behaviour components, the actual control action can be constructed based on the individual control actions of the component behaviours. In this case the control action is either related to an individual behaviour component or to a fusion of behaviour components based on their relevance to the actual situation. This paper adapts the concept of fuzzy automaton for achieving the decision related to the relevance of the behaviour components in the task of the navigation of an autonomous vehicle. In the structure applied, the relevance of the behaviour components is approximated by a fuzzy rule interpolation (FRI, namely the FIVE method) based fuzzy automaton. The main reason for the FRI application is the state-transition rule-base simplification of the fuzzy automaton. In case of FRI, sparse rule bases (incomplete rule bases) are acceptable, because derivable rules can be omitted intentionally, saving construction time and reducing the complexity of the state-transition rule-base. The paper also provides a brief overview of Behaviour based Control and fuzzy rule interpolation (FRI). For demonstration purposes the paper gives a simple example of state-transition rulebase construction in case of the vehicle navigation task mentioned.