RoboMAX: Robotic Mission Adaptation eXemplars
Paper in proceeding, 2021
Emerging and future applications of robotic systems pose unique self-adaptation challenges. To support the research needed to address these challenges, we provide an extensible repository of robotic mission adaptation exemplars. Co-designed with robotic application stakeholders including researchers, developers, operators, and end-users, our repository captures key sources of uncertainty, adaptation concerns, and other distinguishing characteristics of such applications. An online form enables external parties to supply new exemplars for curation and inclusion into the repository. We envisage that our RoboMAX repository will enable the development, evaluation, and comparison of self-adaptation approaches for the robotic systems domain.
Author
Mehrnoosh Askarpour
McMaster University
Christos Tsigkanos
Vienna University of Technology
Claudio Menghi
University of Luxembourg
Radu Calinescu
University of York
Patrizio Pelliccione
Gran Sasso Science Institute (GSSI)
University of Gothenburg
Sergio García Gonzalo
University of Gothenburg
Ricardo Diniz Caldas
Cyber Physical Systems
Tim J. Von Oertzen
Johannes Kepler University of Linz (JKU)
M. Wimmer
Johannes Kepler University of Linz (JKU)
Luca Berardinelli
Johannes Kepler University of Linz (JKU)
Matteo Rossi
Polytechnic University of Milan
Marcello M. Bersani
Polytechnic University of Milan
Gabriel S. Rodrigues
University of Brasilia
Proceedings - 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2021
245-251 9462005
9781665402897 (ISBN)
2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2021
Virtual, Online, ,
Virtual, Online, ,
Subject Categories
Information Systemes, Social aspects
Robotics
Computer Science
DOI
10.1109/SEAMS51251.2021.00040