Mission planner for multiple AUVs: Verification procedures combining simulations and experiments

Buadu, Stephanie; Schjølberg, Ingrid; Mo-Bjørkelund, Tore

doi:10.1109/auv.2018.8729793

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…The C2 assumes a many-to-many relationship between pilots and vehicles, which may be deployed for months at a time. The Norwegian University of Science and Technology Applied Underwater Laboratory have developed a Mission Control System (MCS) (Buadu et al, 2018) in collaboration with the LSTS toolchain. The main purpose of the MCS is to control formations of fleets of vehicles.…”

Section: Web-based Piloting Infrastructurementioning

confidence: 99%

Oceanids C2: An Integrated Command, Control, and Data Infrastructure for the Over-the-Horizon Operation of Marine Autonomous Systems

et al. 2020

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Long-range Marine Autonomous Systems (MAS), operating beyond the visual line-of-sight of a human pilot or research ship, are creating unprecedented opportunities for oceanographic data collection. Able to operate for up to months at a time, periodically communicating with a remote pilot via satellite, long-range MAS vehicles significantly reduce the need for an expensive research ship presence within the operating area. Heterogeneous fleets of MAS vehicles, operating simultaneously in an area for an extended period of time, are becoming increasingly popular due to their ability to provide an improved composite picture of the marine environment. However, at present, the expansion of the size and complexity of these multi-vehicle operations is limited by a number of factors: (1) custom control-interfaces require pilots to be trained in the use of each individual vehicle, with limited cross-platform standardization; (2) the data produced by each vehicle are typically in a custom vehicle-specific format, making the automated ingestion of observational data for near-real-time analysis and assimilation into operational ocean models very difficult; (3) the majority of MAS vehicles do not provide machine-to-machine interfaces, limiting the development and usage of common piloting tools, multi-vehicle operating strategies, autonomous control algorithms and automated data delivery. In this paper, we describe a novel piloting and data management system (C2) which provides a unified web-based infrastructure for the operation of long-range MAS vehicles within the UK's National Marine Equipment Pool. The system automates the archiving, standardization and delivery of near-real-time science data and associated metadata from the vehicles to end-users and Global Data Assembly Centers mid-mission. Through the use and promotion of standard data formats and machine interfaces throughout the C2 system, we seek to enable future opportunities to collaborate with both the marine science and robotics communities to maximize the delivery of high-quality oceanographic data for world-leading science.

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Section: Web-based Piloting Infrastructurementioning

confidence: 99%

Oceanids C2: An Integrated Command, Control, and Data Infrastructure for the Over-the-Horizon Operation of Marine Autonomous Systems

et al. 2020

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“…With the continuous development of technology, people have conducted research on mission planning problems at different levels. Both mission planning and autonomous task planning have been explored in depth and widely applied in various fields, such as aircraft mission planning, ground robot task planning, and ground unmanned combat command system task planning [5][6][7][8][9]. Compared with a simple planning problem, UUV mission planning research started recently, and it can learn from the more mature technology research in the fields of robots, aircraft, satellites, and so on.…”

Section: Introductionmentioning

confidence: 99%

Man-in-the-Loop Control and Mission Planning for Unmanned Underwater Vehicles

Han,

Wang,

Yuan

et al. 2024

JMSE

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UUVs (unmanned underwater vehicles) perform tasks in the marine environment under direction from a commander through a mother ship control system. In cases where communication is available, a UUV task re-planning system was designed to ensure task completion despite uncertain events faced by UUVs. First, the XML language standardizes the expression of UUV task elements. Second, considering the time sequence and spatial path planning requirements of human-supervised UUV control tasks, time sequence planning based on a genetic algorithm and spatial path planning based on an improved genetic algorithm were designed to plan near-optimal approximate spatial paths for control tasks. Third, uncertainties encountered during UUV task execution were classified so that the commander could adjust according to the situation or invoke the control task re-planning algorithm to re-plan. Finally, a simulation platform was built using the QT development environment to simulate human-supervised UUV control task planning and re-planning, verifying the algorithm’s design effectiveness.

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Parent–child‐based navigation method of multiple autonomous underwater vehicles for an underwater self‐completed survey

Matsuda

Fujita

Hamamatsu

et al. 2021

Journal of Field Robotics

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This study proposes a navigation method of multiple autonomous underwater vehicles (AUVs) where low-cost AUVs (child AUVs) estimate their self-states including their position, yaw angle, and horizontal moving velocity accurately thanks to a single high-performance AUV (parent AUV) without any external support. Since the child AUVs have only simple navigational sensors, positioning performance is not enough. The parent AUV, on the other hand, can conduct accurate self-state estimation using high-grade navigational sensors without any external support. The parent AUV supports the child AUVs through all processes of deployment, surveying, recovery, and surfacing. This study focuses on the accurate positioning method for the phase of the surveying. The child AUVs have acoustic devices for positioning and communication or cameras; hence, they build a parent-centered wireless positioning and communication network and can also estimate their self-states as accurately as the parent AUV, thanks to the positioning relative to the parent AUV.Field experiments with AUVs were conducted in a deep sea (hydrothermal vent field) and a shallow area. We confirmed that long-range navigation could be achieved while keeping an accuracy that is 5-10 times greater than that achieved by the child AUV alone based on state estimation using sensor data from the experiments in postprocessing. The performance of the proposed system does not depend on the child AUV's performance. We also verified that the proposed method has a certain scalability and a high-level performance in terms of accuracy, efficiency, and cost by a comparison with other existing navigation methods.

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Mission planner for multiple AUVs: Verification procedures combining simulations and experiments

Cited by 3 publications

References 5 publications

Oceanids C2: An Integrated Command, Control, and Data Infrastructure for the Over-the-Horizon Operation of Marine Autonomous Systems

Oceanids C2: An Integrated Command, Control, and Data Infrastructure for the Over-the-Horizon Operation of Marine Autonomous Systems

Man-in-the-Loop Control and Mission Planning for Unmanned Underwater Vehicles

Parent–child‐based navigation method of multiple autonomous underwater vehicles for an underwater self‐completed survey

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