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C. Menghi, C. Tsigkanos, P. Pelliccione, C. Ghezzi, T. Berger:
"Specification Patterns for Robotic Missions";
IEEE Transactions on Software Engineering, Volume 47 (2021), Issue 10; 2208 - 2224.

Mobile and general-purpose robots increasingly support everyday life, requiring dependable robotics control software. Creating such software mainly amounts to implementing complex behaviors known as missions. Recognizing this need, a large number of domain-specific specification languages has been proposed. These, in addition to traditional logical languages, allow the use of formally specified missions for synthesis, verification, simulation or guiding implementation. For instance, the logical language LTL is commonly used by experts to specify missions as an input for planners, which synthesize a robot's required behavior. Unfortunately, domain-specific languages are usually tied to specific robot models, while logical languages such as LTL are difficult to use by non-experts. We present a catalog of 22 mission specification patterns for mobile robots, together with tooling for instantiating, composing, and compiling the patterns to create mission specifications. The patterns provide solutions for recurrent specification problems; each pattern details the usage intent, known uses, relationships to other patterns, and-most importantly-a template mission specification in temporal logic. Our tooling produces specifications expressed in the temporal logics LTL and CTL to be used by planners, simulators or model checkers. The patterns originate from 245 mission requirements extracted from the robotics literature, and they are evaluated upon a total of 441 real-world mission requirements and 1251 mission specifications. Five of these reflect scenarios defined with two well-known industrial partners developing human-size robots. We further validate our patterns´ correctness with simulators and two different types of real robots.

Mission specification, pattern catalog, robotic mission, model driven engineering

http://dx.doi.org/10.1109/TSE.2019.2945329