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Optimized environment exploration for autonomous underwater vehicles

Vidal, Eduard, Hernández, Juan David, Istenic, Klemen and Carreras, Marc 2018. Optimized environment exploration for autonomous underwater vehicles. Presented at: IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Queensland, Australia, 21-25 May 2018. 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, pp. 6409-6416. 10.1109/ICRA.2018.8460919

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Achieving full autonomous robotic environment exploration in the underwater domain is very challenging, mainly due to noisy acoustic sensors, high localization error, control disturbances of the water and lack of accurate un- derwater maps. In this work we present a robotic exploration algorithm for underwater vehicles that does not rely on prior information about the environment. Our method has been greatly influenced by many robotic exploration, view planning and path planning algorithms. The proposed method constitutes a significant improvement over our previous work [1]: Firstly, we refine our exploration approach to improve robustness; Secondly, we propose an alternative map representation based on the quadtree data structure that allows different relevant queries to be performed efficiently, reducing the computational cost of the viewpoint generation process; Thirdly, we present an algorithm that is capable of generating consistent maps even when noisy sonar data is used. The aforementioned contributions have increased the reliability of the algorithm, allowing new real experiments performed in artificial structures but also in more challenging natural environments, from which we provide a 3D reconstruction to show that with this algorithm full optical coverage is obtained.

Item Type: Conference or Workshop Item (Paper)
Date Type: Published Online
Status: Published
Schools: Engineering
Additional Information: "© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."
Publisher: IEEE
ISBN: 9781538630815
ISSN: 2577-087X
Date of First Compliant Deposit: 19 February 2021
Date of Acceptance: 12 January 2018
Last Modified: 19 Feb 2021 16:51

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