  Most autonomous robotic agents use logic inference to keep themselves to safe
and permitted behaviour. Given a set of rules, it is important that the robot
is able to establish the consistency between its rules, its perception-based
beliefs, its planned actions and their consequences. This paper investigates
how a robotic agent can use model checking to examine the consistency of its
rules, beliefs and actions. A rule set is modelled by a Boolean evolution
system with synchronous semantics, which can be translated into a labelled
transition system (LTS). It is proven that stability and consistency can be
formulated as computation tree logic (CTL) and linear temporal logic (LTL)
properties. Two new algorithms are presented to perform realtime consistency
and stability checks respectively. Their implementation provides us a
computational tool, which can form the basis of efficient consistency checks
on-board robots.
