Authors: Martin Aubard, Sergio Quijano, Olaya Álvarez-Tuñón, László Antal, Maria Costa, Yury Brodskiy

Published on: February 06, 2024

Impact Score: 8.07

Arxiv code: Arxiv:2402.04045

Summary

• What is new: A framework utilizing Behavior Trees for modeling and BehaVerify for mission plan verification to increase the flexibility and autonomy of underwater inspection missions.
• Why this is important: Current underwater inspection missions rely on predefined plans, limiting flexibility and success in unexpected scenarios.
• What the research proposes: A new framework with an AI-enabled algorithm for autonomous pipeline inspection leveraging Behavior Trees for real-time plan adjustments.
• Results: In simulations, the framework and algorithm improved the safety and success of autonomous underwater pipeline inspections.

Technical Details

Technological frameworks used: Behavior Trees (BTs), BehaVerify

Models used: AI-enabled algorithm for pipeline data collection

Data used: Simulated underwater environments

Potential Impact

Underwater inspection services, offshore infrastructure management companies, and autonomous underwater vehicle manufacturers.

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