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, ,

Subject Categories

Information Systemes, Social aspects

Robotics

Computer Science

DOI

10.1109/SEAMS51251.2021.00040

More information

Latest update

9/16/2021