PyBDR: Set-Boundary Based Reachability Analysis Toolkit in Python

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorDing, Jianqiangen_US
dc.contributor.authorWu, Taoranen_US
dc.contributor.authorLiang, Zhenen_US
dc.contributor.authorXue, Baien_US
dc.contributor.departmentDepartment of Electrical Engineering and Automationen
dc.contributor.editorPlatzer, Andreen_US
dc.contributor.editorRozier, Kristin Yvonneen_US
dc.contributor.editorPradella, Matteoen_US
dc.contributor.editorRossi, Matteoen_US
dc.contributor.groupauthorNonlinear Systems and Controlen
dc.contributor.organizationCAS - Institute of Softwareen_US
dc.contributor.organizationNational University of Defense Technologyen_US
dc.date.accessioned2024-10-09T06:06:53Z
dc.date.available2024-10-09T06:06:53Z
dc.date.issued2025en_US
dc.descriptionPublisher Copyright: © The Author(s) 2025.
dc.description.abstractWe present PyBDR, a Python reachability analysis toolkit based on set-boundary analysis, which centralizes on widely-adopted set propagation techniques for formal verification, controller synthesis, state estimation, etc. It employs boundary analysis of initial sets to mitigate the wrapping effect during computations, thus improving the performance of reachability analysis algorithms without significantly increasing computational costs. Beyond offering various set representations such as polytopes and zonotopes, our toolkit particularly excels in interval arithmetic by extending operations to the tensor level, enabling efficient parallel interval arithmetic computation and unifying vector and matrix intervals into a single framework. Furthermore, it features symbolic computation of derivatives of arbitrary order and evaluates them as real or interval-valued functions, which is essential for approximating behaviours of nonlinear systems at specific time instants. Its modular architecture design offers a series of building blocks that facilitate the prototype development of reachability analysis algorithms. Comparative studies showcase its strengths in handling verification tasks with large initial sets or long time horizons. The toolkit is available at https://github.com/ASAG-ISCAS/PyBDR.en
dc.description.versionPeer revieweden
dc.format.extent18
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationDing, J, Wu, T, Liang, Z & Xue, B 2025, PyBDR: Set-Boundary Based Reachability Analysis Toolkit in Python. in A Platzer, K Y Rozier, M Pradella & M Rossi (eds), Formal Methods - 26th International Symposium, FM 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14934 LNCS, Springer, pp. 140-157, International Symposium on Formal Methods, Milan, Italy, 09/09/2024. https://doi.org/10.1007/978-3-031-71177-0_10en
dc.identifier.doi10.1007/978-3-031-71177-0_10en_US
dc.identifier.isbn978-3-031-71176-3
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.otherPURE UUID: 7ff2f6e9-90e1-47c0-b9c6-aa1738b9657aen_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/7ff2f6e9-90e1-47c0-b9c6-aa1738b9657aen_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85205117344&partnerID=8YFLogxK
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/160802361/978-3-031-71177-0_10.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/131134
dc.identifier.urnURN:NBN:fi:aalto-202410096665
dc.language.isoenen
dc.relation.ispartofInternational Symposium on Formal Methodsen
dc.relation.ispartofseriesFormal Methods - 26th International Symposium, FM 2024, Proceedingsen
dc.relation.ispartofseriespp. 140-157en
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; Volume 14934 LNCSen
dc.rightsopenAccessen
dc.titlePyBDR: Set-Boundary Based Reachability Analysis Toolkit in Pythonen
dc.typeA4 Artikkeli konferenssijulkaisussafi
dc.type.versionpublishedVersion

Files