MORAP: a Modular Robotic Arm Platform for Teaching and Experimenting with Equation-based Modeling Languages [Work in Progress]
2016 (English)In: Proceedings of 7th International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools (EOOLT), ACM Digital Library, 2016, 27-30 p.Conference paper (Refereed)
Equation-based object-oriented (EOO) modeling and simu- lation techniques have in the last decades gained significant attention both in academia and industry. One of the key properties of EOO languages is modularity, where different components can be developed independently and then connected together to form a complete acausal model. However, extensive modeling without explicit model validation together with a real physical system can result in incorrect assumptions and false conclusions. In particular, in an educational and research setting, it is vital that students experiment both with equation-based models and the real system that is being modeled. In this work-in-progress paper, we present a physical experimental robotic arm platform that is designed for teaching and research. Similar to EOO models, the robotic arm is modular, meaning that its parts can be reconfigured and composed together in various settings, and used for different experiments. The platform is completely open source, where electronic schematics, CAD models for 3D printing, controller software, and component specifications are available on GitHub. The vision is to form a community, where new open source components are continuously added, to enable an open and freely available physical experimental platform for EOO languages.
Place, publisher, year, edition, pages
ACM Digital Library, 2016. 27-30 p.
Modeling, simulations, equations, robotic arm
Research subject Computer Science
IdentifiersURN: urn:nbn:se:kth:diva-186048DOI: 10.1145/2904081.2904085ScopusID: 2-s2.0-84976371904ISBN: 978-1-4503-4202-5OAI: oai:DiVA.org:kth-186048DiVA: diva2:925056
EOOLT 2016, April 18, Milano, Italy
QC 201609122016-04-292016-04-292016-09-12Bibliographically approved