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Coverage-driven verification — An approach to verify code for robots that directly interact with humans

Pipe, Anthony; Araiza-Illan, Dejanira; Western, David; Pipe, Anthony G.; Eder, Kerstin

Authors

Anthony Pipe

Dejanira Araiza-Illan

David Western David.Western@uwe.ac.uk
Wallscourt Fellow in Health Technology

Kerstin Eder



Abstract

© Springer International Publishing Switzerland 2015. Collaborative robots could transform several industries, such as manufacturing and healthcare, but they present a significant challenge to verification. The complex nature of their working environment necessitates testing in realistic detail under a broad range of circumstances. We propose the use of Coverage-Driven Verification (CDV) to meet this challenge. By automating the simulation-based testing process as far as possible, CDV provides an efficient route to coverage closure. We discuss the need, practical considerations, and potential benefits of transferring this approach from microelectronic design verification to the field of human-robot interaction. We demonstrate the validity and feasibility of the proposed approach by constructing a custom CDV testbench and applying it to the verification of an object handover task.

Journal Article Type Conference Paper
Publication Date Jan 1, 2015
Journal Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Print ISSN 0302-9743
Electronic ISSN 1611-3349
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 9434
Pages 69-84
Book Title Hardware and Software: Verification and Testing
APA6 Citation Pipe, A., Araiza-Illan, D., Western, D., Pipe, A. G., & Eder, K. (2015). Coverage-driven verification — An approach to verify code for robots that directly interact with humans. Lecture Notes in Artificial Intelligence, 9434, 69-84. https://doi.org/10.1007/978-3-319-26287-1_5
DOI https://doi.org/10.1007/978-3-319-26287-1_5
Keywords robot-human interaction, code verification, coverage-driven
Publisher URL http://dx.doi.org/10.1007/978-3-319-26287-1_5
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