A Corroborative Approach to Verification and Validation of Human--Robot Teams
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Abstract (arXiv)
We present an approach for the verification and validation (V&V) of robot assistants in the context of human-robot interactions (HRI), 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. We demonstrate our corroborative V&V approach through a handover task, the most critical part of a complex cooperative manufacturing scenario, for which we propose some safety and liveness requirements to verify and validate. We construct formal models, simulations and an experimental test rig for the HRI. To capture requirements we use temporal logic properties, assertion checkers and textual descriptions. This combination of approaches allows V&V of the HRI task at different levels of modelling detail and thoroughness of exploration, thus overcoming the individual limitations of each technique. 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 HRI 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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Aug 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 1; 2025: 1; 2026: 1.
6 papers.
- 2021Coverage based testing for V&V and Safety Assurance of Self-driving Autonomous Vehicles: A Systematic Literature Reviewcited by 8
- 2023Learning Formal Specifications from Membership and Preference Queriescited by 3
- 2023Assessing Trustworthiness of Autonomous Systemscited by 1
- 2024Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validationcited by 1
- 2025Autonomy and Safety Assurance in the Early Development of Robotics and Autonomous Systemscited by 0
- 2026Engineering Reliable Autonomous Systems: Challenges and Solutionscited by 0
- 2026Engineering Reliable Autonomous Systems: Challenges and Solutions22 Jun 2026
- 2025Autonomy and Safety Assurance in the Early Development of Robotics and Autonomous Systems30 Jan 2025
- 2024Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation22 Jul 2024
- 2023Learning Formal Specifications from Membership and Preference Queries19 Jul 2023
- 2023Assessing Trustworthiness of Autonomous Systems5 May 2023
- 2021Coverage based testing for V&V and Safety Assurance of Self-driving Autonomous Vehicles: A Systematic Literature Review7 Mar 2021