Testing robots using CSP

This paper presents a technique for automatic generation of tests for robotic systems based on a domain-specific notation called RoboChart. This is a UML-like diagrammatic notation that embeds a component model suitable for robotic systems, and supports the definition of behavioural models using enriched state machines that can feature time properties. The formal semantics of RoboChart is given using tockCSP, a discrete-time variant of the process algebra CSP. In this paper, we use the example of a simple drone to illustrate an approach to generate tests from RoboChart models using a mutation tool called Wodel. From mutated models, tests are generated using the CSP model checker FDR. The testing theory of CSP justifies the soundness of the tests

Implementation relations and testing for cyclic systems: adding probabilities

This paper concerns the systematic testing of robotic control software based on state-based models. We focus on cyclic systems that typically receive inputs (values from sensors), perform computations, produce outputs (sent to actuators) and possibly change state. We provide a testing theory for such cyclic systems where time can be represented and probabilities are used to quantify non-deterministic choices, making it possible to model probabilistic algorithms. In addition, refusals, the inability of a system to perform a set of actions, are taken into account. We consider several possible testing scenarios. For example, a tester might only be able to passively observe a sequence of events and so cannot check probabilities, while in another scenario a tester might be able to repeatedly apply a test case and so estimate the probabilities of sequences of events. These different testing scenarios lead to a range of implementation relations (notions of correctness). As a consequence, this paper provides formal definitions of implementation relations that can form the basis of sound automated testing in a range of testing scenarios. We also validate the implementation relations by showing how observers can be used to provide an alternative but equivalent characterisation

RoboWorld : Verification of Robotic Systems with Environment in the Loop

A robot affects and is affected by its environment, so that typically its behaviour depends on properties of that environment. For verification, we need to formalise those properties. Modelling the environment is very challenging, if not impossible, but we can capture assumptions. Here, we present RoboWorld, a domain-specific controlled natural language with a process algebraic semantics that can be used to define (a) operational requirements, and (b) environment interactions of a robot. RoboWorld is part of the RoboStar framework for verification of robotic systems. In this article, we define RoboWorld's syntax and hybrid semantics, and illustrate its use for capturing operational requirements, for automatic test generation, and for proof. We also present a tool that supports the writing of RoboWorld documents. Since RoboWorld is a controlled natural language, it complements the other RoboStar notations in being accessible to roboticists, while at the same time benefitting from a formal semantics to support rigorous verification (via testing and proof)