LAUSR

With many applications across domains as diverse as logistics, healthcare, and agriculture, service robots are in increasingly high demand. Nevertheless, the designers of these robots often struggle with specifying their tasks in a way that is both human-understandable and sufficiently precise to enable automated verification and planning of robotic missions. Recent research has addressed this problem for the functional aspects of robotic missions through the use of mission specification patterns. These patterns support the definition of robotic missions involving, for instance, the patrolling of a perimeter, the avoidance of unsafe locations within an area, or reacting to specific events. Our article introduces a catalog of QUantitAtive RoboTic mission spEcificaTion patterns (QUARTET) that tackles the complementary and equally important challenge of specifying the reliability, performance, resource usage, and other key quantitative properties of robotic missions. Identified using a methodology that included the analysis of 73 research papers published in 17 leading software engineering and robotics venues between 2014–2021, our 22 QUARTET patterns are defined in a tool-supported domain-specific language. As such, QUARTET enables: (i) the precise definition of quantitative robotic-mission requirements and (ii) the translation of these requirements into probabilistic reward computation tree logic (PRCTL), supporting their formal verification and automated planning of robotic missions. We demonstrate the applicability of QUARTET by showing that it supports the specification of over 95% of the quantitative robotic mission requirements from a systematically selected set of recent research papers, of which 75% can be automatically translated into PRCTL for the purposes of verification through model checking and mission planning.