Reachset Conformance of Forward Dynamic Models for the Formal Analysis of Robots

Stefan B. Liu, Matthias Althoff

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations

Abstract

Model-based design of robotic systems has many advantages, among them faster development cycles and reduced costs due to early detections of design flaws. Approximate models are sufficient for many classical robotic applications; however, they no longer suffice for safety-critical applications. For instance, a dangerous situation which has not been detected by model-based testing might occur in a human-robot coexistence scenario since models do not exactly replicate behaviors of real systems-this problem arises no matter how accurate a model is, since even disturbances and sensor noise can cause a mismatch. We address this issue by adding nondeterminism to robotic models and by computing the whole set of possible behaviors using reachability analysis. By using reachset conformance, we automatically adjust the required non-determinism so that all recorded behaviors are captured. For the first time this approach is demonstrated for a real robot.

Original languageEnglish
Title of host publication2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages370-376
Number of pages7
ISBN (Electronic)9781538680940
DOIs
StatePublished - 27 Dec 2018
Event2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018 - Madrid, Spain
Duration: 1 Oct 20185 Oct 2018

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
Country/TerritorySpain
CityMadrid
Period1/10/185/10/18

Fingerprint

Dive into the research topics of 'Reachset Conformance of Forward Dynamic Models for the Formal Analysis of Robots'. Together they form a unique fingerprint.

Cite this