Analysing RoboChart with probabilities

Robotic systems have applications in many real-life scenarios, ranging from household cleaning to critical operations. RoboChart is a graphical language for describing robotic controllers designed specifically for autonomous and mobile robots, providing architectural constructs to identify the requirements for a robotic platform. It also provides a formal semantics in CSP. RoboChart has a probabilistic operator (P) but no associated probabilistic CSP semantics. When (P) is used, currently a non-deterministic choice (Π) is used as semantics; this is a conservative semantics but it does not allow the analysis of stochastic properties. In this paper we define the semantics of the operator in terms of the probabilistic CSP operator ⊞. We also show how this augmented CSP semantics for RoboChart can be translated into the PRISM probabilistic language to be able to check stochastic properties

Probabilistic modelling and verification using RoboChart and PRISM

RoboChart is a timed domain-specific language for robotics, distinctive in its support for automated verification by model checking and theorem proving. Since uncertainty is an essential part of robotic systems, we present here an extension to RoboChart to model uncertainty using probabilism. The extension enriches RoboChart state machines with probability through a new construct: probabilistic junctions as the source of transitions with a probability value. RoboChart has an accompanying tool, called RoboTool, for modelling and verification of functional and real-time behaviour. We present here also an automatic technique, implemented in RoboTool, to transform a RoboChart model into a PRISM model for verification. We have extended the property language of RoboTool so that probabilistic properties expressed in temporal logic can be written using controlled natural language