An approach to apply Automated Acceptance Testing for Industrial Robotic Systems

Abstract

Industrial robotic systems (IRS) are systems composed of industrial robots that automate industrial processes. They execute repetitive tasks with high accuracy, replacing or supporting dangerous jobs. Consequently, a low failure rate is crucial in IRS. However, to the best of our knowledge, there is a lack of automated software testing for industrial robots. In this paper, we describe a test strategy implementation to apply BDD to automate acceptance testing for IRS.