RT Conference Proceedings
T1 Assumptions and Guarantees for Composable Models in Papyrus for Robotics
A1 Martinez, Jabier
A1 Ruiz, Alejandra
A1 Radermacher, Ansgar
A1 Tonetta, Stefano
AB The separation of concerns helps to manage the intrinsic complexity of defining robotics components, systems and missions. This separation of concerns is supported by the Rob-MoSys modelling approach addressing both the modelling needs of the robotics domain and identifying the involved stakeholders and required expertise. In this multi-stakeholder context, there are pressing concerns about non-functional characteristics including safety aspects (e.g., collaborative robots, increasing risks to humans and the environment where robotic systems operate). It is of special interest to explicitly establish the non-functional assumptions and guarantees. This assures that the their validity can be automatically evaluated, in particular during the definition of a system as a composition of several component definitions. We present how we extended one of the RobMoSys implementations, Papyrus for Robotics, for contracts modelling and assertions validation. Notably this includes the meta-modelling decisions to allow extensibility for assertion languages.
PB Institute of Electrical and Electronics Engineers Inc.
SN 9781665444743
YR 2021
FD 2021-06
LK https://hdl.handle.net/11556/2812
UL https://hdl.handle.net/11556/2812
LA eng
NO Martinez , J , Ruiz , A , Radermacher , A & Tonetta , S 2021 , Assumptions and Guarantees for Composable Models in Papyrus for Robotics . in Proceedings - 2021 IEEE/ACM 3rd International Workshop on Robotics Software Engineering, RoSE 2021 . , 9474426 , Proceedings - 2021 IEEE/ACM 3rd International Workshop on Robotics Software Engineering, RoSE 2021 , Institute of Electrical and Electronics Engineers Inc. , pp. 1-4 , 3rd IEEE/ACM International Workshop on Robotics Software Engineering, RoSE 2021 , Virtual, Online , 2/06/21 . https://doi.org/10.1109/RoSE52553.2021.00007
NO conference
NO Publisher Copyright: © 2021 IEEE.
NO ACKNOWLEDGMENT This work has been funded by RobMoSys (EU H2020 No. 732410) through the SafeCC4Robot technical project. Thanks to Angel López, Elixabete Ostolaza, Matteo Morelli and Huascar Espinoza for their help.
DS TECNALIA Publications
RD 30 jul 2024