A corroborative approach to verification and validation of human–robot teams

Research output: Contribution to journalArticlepeer-review

  • External authors:
  • Matt Webster
  • David Western
  • Dejanira Araiza-Illan
  • Kerstin Eder
  • Anthony G. Pipe

Abstract

We present an approach for the verification and validation (V&V) of robot assistants in the context of human–robot interactions, to demonstrate their trustworthiness through corroborative evidence of their safety and functional correctness. Key challenges include the complex and unpredictable nature of the real world in which assistant and service robots operate, the limitations on available V&V techniques when used individually, and the consequent lack of confidence in the V&V results. Our approach, called corroborative V&V, addresses these challenges by combining several different V&V techniques; in this paper we use formal verification (model checking), simulation-based testing, and user validation in experiments with a real robot. This combination of approaches allows V&V of the human–robot interaction task at different levels of modeling detail and thoroughness of exploration, thus overcoming the individual limitations of each technique. We demonstrate our approach through a handover task, the most critical part of a complex cooperative manufacturing scenario, for which we propose safety and liveness requirements to verify and validate. Should the resulting V&V evidence present discrepancies, an iterative process between the different V&V techniques takes place until corroboration between the V&V techniques is gained from refining and improving the assets (i.e., system and requirement models) to represent the human–robot interaction task in a more truthful manner. Therefore, corroborative V&V affords a systematic approach to “meta-V&V,” in which different V&V techniques can be used to corroborate and check one another, increasing the level of certainty in the results of V&V.

Bibliographical metadata

Original languageEnglish
Pages (from-to)73-99
Number of pages27
JournalThe International Journal of Robotics Research
Volume39
Issue number1
Early online date25 Nov 2019
DOIs
Publication statusPublished - 1 Jan 2020

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