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Development of a multi-platform obstacle avoidance system for autonomous underwater vehicles

Fanelli, Francesco; Fenucci, Davide; Marlow, Rachel; Pebody, Miles; Phillips, Alexander B.. 2020 Development of a multi-platform obstacle avoidance system for autonomous underwater vehicles. In: IEEE/OES Autonomous Underwater Vehicles Symposium (AUV) 2020, St Johns, NL, Canada, 30 Sep - 2 Oct 2020. 1-6.

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Abstract/Summary

Undertaking world-class ocean science requires data gathering in some of the world’s most extreme environments, such as under polar ice, deep benthic habitats and underwater canyons. Autonomous Underwater Vehicles (AUVs) are often employed for these tasks, as these stable, untethered, vehicles are able to access areas not reachable with conventional ship-based sampling methods. It is easy to understand how deployments in such scenarios require the AUV to be equipped with appropriate sensors to perceive obstacles within its environment as well as suitable collision avoidance control schemes to maintain safe operation.The Marine Autonomous and Robotic Systems (MARS) group at the National Oceanography Centre (NOC) develops and operates multiple AUVs suited for missions in a range of extreme environments. Recently, a considerable effort has been made to develop the NOC On-board Control System (OCS) for AUVs, a unified software architecture able to adapt to different platforms and to provide greater flexibility and extensibility in terms of underwater autonomy. Within this framework, a new Obstacle Avoidance System (OAS) is being developed. The goal is to design a flexible and modular system able to work effectively with different vehicles and in different scenarios, and to satisfy diverse science requirements.This paper will describe the OAS and its components, its integration within the OCS, and its interaction with the preexisting on-board autonomy and guidance systems when dealing with collisions and obstacles in the context of autonomous navigation.

Item Type: Publication - Conference Item (Paper)
Digital Object Identifier (DOI): https://doi.org/10.1109/AUV50043.2020.9267942
Date made live: 10 Dec 2020 15:33 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/529139

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