Safe Adaptation of Cobotic Cells based on Petri Nets

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Abstract

Collaborative robotic cells combine human skills with the latest advancements in robotic accuracy and reliability. Cobotic cell parts are distributed and adapt their behavior to changing tasks and environments. The specific missions of cobotic cells, depend on their field of application, but are critical for human safety, which introduces complexity, increasing testing and development effort. Component-based software engineering is used to manage complexity, but ensuring safety and correctness requires verification and validation, which is complex and demanding to re-ensure, when composed behavior changes. This also applies to the widely used middleware Robot Operating System (ROS), where existing approaches only model high level communication or integrate models. Also, verification of cobotic cells must reflect their context-Adaptivity, to check safety critical reactions to contexts-changes. To overcome these inhibitors, a model-driven development approach based on Petri nets is proposed, modeling central aspects of ROS-based cobotic cells. By using formal models, the testing effort at development time is reduced, because global behavior remains formally proven, and only local components have to be retested. Within this work, the plans for this model-driven software approach are reported.

Details

Original languageEnglish
Title of host publicationProceedings - 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages43-47
Number of pages5
ISBN (electronic)978-1-4503-9305-8
Publication statusPublished - 2022
Peer-reviewedYes

Conference

Title17th Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2022
Duration18 - 20 May 2022
CityPittsburgh
CountryUnited States of America

External IDs

Scopus 85134180166

Keywords

Keywords

  • Context Adaptation, Petri Nets, Robot Operating System, Robotics