On the Verification and Validation of AI Navigation Algorithms

• URL: http://arxiv.org/abs/2101.06091v1
• Date: Fri, 15 Jan 2021 13:15:23 GMT
• Title: On the Verification and Validation of AI Navigation Algorithms
• Authors: Ivan Porres, Sepinoud Azimi, S\'ebastien Lafond, Johan Lilius, Johanna Salokannel, Mirva Salokorpi
• Abstract summary: We perform a systematic mapping study to find research works proposing new algorithms for autonomous navigation and collision avoidance. We have extracted what verification and validation approaches have been applied on these algorithms. We propose the use of a systematic scenario-based testing approach to validate navigation algorithms extensively.
• Score: 0.22509387878255815
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper explores the state of the art on to methods to verify and validate navigation algorithms for autonomous surface ships. We perform a systematic mapping study to find research works published in the last 10 years proposing new algorithms for autonomous navigation and collision avoidance and we have extracted what verification and validation approaches have been applied on these algorithms. We observe that most research works use simulations to validate their algorithms. However, these simulations often involve just a few scenarios designed manually. This raises the question if the algorithms have been validated properly. To remedy this, we propose the use of a systematic scenario-based testing approach to validate navigation algorithms extensively.

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