Fuzz Testing in Behavior-Based Robotics

Rodrigo Delgado, Miguel Campusano*, Alexandre Bergel

*Kontaktforfatter

Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

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Abstract

The behavior of a robot is typically expressed as a set of source code files written using a programming language. As for any software engineering activity, programming robotic behaviors is a complex and error-prone task. This paper propose a methodology that aims to reduce the cost of producing a reliable software describing a robotic behavior by automatically testing it. We employ a fuzz testing technique to stress software components with randomly generated data. By applying fuzz testing to a complex robotic-software, we identified errors related to the coding, the way data is handled, the logic of the robotic behavior, and the initialization of architectural components. Furthermore, a panel of experts acquainted with the analyzed behavior have highlighted the relevance and the significance of our findings. Our fuzzer operates on the SMACH and ROS frameworks and it is available under the MIT public open source license.

OriginalsprogEngelsk
Titel2021 IEEE International Conference on Robotics and Automation, ICRA 2021
ForlagIEEE
Publikationsdato2021
Sider9375-9381
ISBN (Elektronisk)9781728190778
DOI
StatusUdgivet - 2021
Begivenhed2021 IEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an, Kina
Varighed: 30. maj 20215. jun. 2021

Konference

Konference2021 IEEE International Conference on Robotics and Automation, ICRA 2021
Land/OmrådeKina
ByXi'an
Periode30/05/202105/06/2021
SponsorBaidu, Biomimetic Intelligence and Robotics, DJI, et al., Mech Mind Robotics Technologies, Toyota Research Institute
NavnIEEE International Conference on Robotics and Automation
Vol/bind2021-May
ISSN1050-4729

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© 2021 IEEE

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