AUV Docking and Recovery with USV: An Experimental Study

Page, Brian R.; Mahmoudian, Nina

doi:10.1109/oceanse.2019.8867159

Cited by 6 publications

(7 citation statements)

References 13 publications

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“…An example of this system appears in [27]. A similar concept is presented in [28] (see Fig. 2) where the AUV has a T-shaped appendage that docks to a V-shaped structure.…”

Section: State Of the Artmentioning

confidence: 92%

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Docking of Non-Holonomic AUVs in Presence of Ocean Currents: A Comparative Survey

et al. 2021

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This paper presents a comparative study of docking algorithms intended for non-holonomic autonomous underwater vehicles, docking in funnel-shaped docking stations, operating under the influence of ocean currents. While descriptive surveys have been already reported in the literature, our goal is to compare the most relevant algorithms through realistic Monte Carlo simulations to provide an insight into their performance. To this aim, a new numerical performance indicator is proposed, which, based on the geometry of the manoeuvre, is able to characterize a successful or unsuccessful docking, providing a metric for comparison. The experimental study is carried out using hardware-in-the-loop simulation by means of the Stonefish simulator, including the dynamic/hydrodynamic model of the Sparus II AUV, models of all internal and external sensors, and the collision geometry representing the docking station.

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“…An example of this system appears in [27]. A similar concept is presented in [28] (see Fig. 2) where the AUV has a T-shaped appendage that docks to a V-shaped structure.…”

Section: State Of the Artmentioning

confidence: 92%

“…This method is based on the pure pursuit controller [36]. Despite having been used by several authors [5,28,37] it is not designed to deal with ocean currents. However, it has been included in this article as a baseline to which the others are compared.…”

Section: A Pure Pursuit Controllermentioning

confidence: 99%

Docking of Non-Holonomic AUVs in Presence of Ocean Currents: A Comparative Survey

et al. 2021

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“…While long-range navigation is a modest problem under the data muling scenario, short-range navigation might have a strong impact on the overall data rates, depending on the employed technology, for ensuring adequate proximity between the DMUs and the SU. Some recent works have looked into the latter problem mostly in the context of AUV docking [47], inspection, intervention [48], and maintenance. However, the tracking performances are hard to model, as they depend on (1) many variables related to control and estimation, (2) random errors corrupting the data from sensors, and (3) often unpredictable environmental disturbances.…”

Section: Auv Navigation and Localizationmentioning

confidence: 99%

A Novel Simulation Platform for Underwater Data Muling Communications Using Autonomous Underwater Vehicles

et al. 2021

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Autonomous Underwater Vehicles (AUVs) are seen as a safe and cost-effective platforms for performing a myriad of underwater missions. These vehicles are equipped with multiple sensors which, combined with their long endurance, can produce large amounts of data, especially when used for video capturing. These data need to be transferred to the surface to be processed and analyzed. When considering deep sea operations, where surfacing before the end of the mission may be unpractical, the communication is limited to low bitrate acoustic communications, which make unfeasible the timely transmission of large amounts of data unfeasible. The usage of AUVs as data mules is an alternative communications solution. Data mules can be used to establish a broadband data link by combining short-range, high bitrate communications (e.g., RF and wireless optical) with a Delay Tolerant Network approach. This paper presents an enhanced version of UDMSim, a novel simulation platform for data muling communications. UDMSim is built upon a new realistic AUV Motion and Localization (AML) simulator and Network Simulator 3 (ns-3). It can simulate the position of the data mules, including localization errors, realistic position control adjustments, the received signal, the realistic throughput adjustments, and connection losses due to the fast SNR change observed underwater. The enhanced version includes a more realistic AML simulator and the antenna radiation patterns to help evaluating the design and relative placement of underwater antennas. The results obtained using UDMSim show a good match with the experimental results achieved using an underwater testbed. UDMSim is made available to the community to support easy and faster evaluation of underwater data muling oriented communications solutions and to enable offline replication of real world experiments.

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“…Therefore, from an operational perspective, the sea state and suitability of the recovery vessel are often the limiting factors in AUV deployments. Various recovery methods exist for safely transitioning AUV through this stage of operations (Page & Mahmoudian, 2019; Sarda & Dhanak, 2018); however, many methods are time‐consuming, limited by sea state, or require significant additional infrastructure (Yazdani et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Expediting recovery of autonomous underwater vehicles in dynamic mission environments: A system‐of‐systems challenge for underwater warfare

Keane

Joiner

Arulampalam

et al. 2022

Journal of Field Robotics

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As autonomous underwater vehicle (AUV) adoption increases, operators demand advanced behaviors from commercial off‐the‐shelf systems. However, new behaviors can often only be deployed operationally once assured. This paper overviews research into expediting recovery to an operator's vessel through a custom homing behavior, demonstrating technology advancement in conjunction with test and evaluation activities. Advanced docking infrastructure and frameworks are still under development, yet current AUV operations require rapid and reliable recovery when mission factors change. Homing is achieved with a directional acoustic transponder providing range and bearing data to the AUV from the operator's vessel. A converted measurement Kalman filter processes range and bearing data that generates dynamic waypoints for the AUV through MOOS‐IvP as a backseat driver; a universal approach and filtering that is unique from prior AUV research. Results from simulations and field trials were analysed through a modular and experimental Test & Evaluation framework that was adopted specifically to help verify and validate the new AUV behavior, including systematic variations in recovery boat manoeuvres. The process includes documented use for the first time in AUV research of combinatorial screening (high throughput testing) and an average standardized residual metric to focus development early, encourage constructive iteration and build operational and engineering trust. Consistent homing was demonstrated with localization within 0.3 m and homing within 1.8 m of a moving digital acoustic transponder.

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AUV Docking and Recovery with USV: An Experimental Study

Cited by 6 publications

References 13 publications

Docking of Non-Holonomic AUVs in Presence of Ocean Currents: A Comparative Survey

Docking of Non-Holonomic AUVs in Presence of Ocean Currents: A Comparative Survey

A Novel Simulation Platform for Underwater Data Muling Communications Using Autonomous Underwater Vehicles

Expediting recovery of autonomous underwater vehicles in dynamic mission environments: A system‐of‐systems challenge for underwater warfare

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