Alternating landmark navigation of multiple AUVs for wide seafloor survey: Field experiment and performance verification

Matsuda, Takumi; Maki, Toshihiro; Sato, Yoshiki; Sakamaki, Takashi; Ura, Tamaki

doi:10.1002/rob.21742

Cited by 12 publications

(5 citation statements)

References 35 publications

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“…It is advisable to carry out a group transition of the released AUVs to the working zone of a predetermined water area (the fourth stage T MAS1 ∈А MUC )) immediately after the release of the last group AUV. The beginning of the motion of each underwater vehicle in the group at a given depth of H MAS1, given course φ MAS1 and with a given speed v MAS1 should be a common team, which is drawn from the USV ACS or from the AUV-leader [17]. One of the main tasks of the automation of this maritime search mission phase is AUVs coordinated motion without loss, i. e. without the collision of the neighboring underwater vehicles (vehicles excessive close approach) and without losing the connection (communication) between them (vehicles excessive distancing).…”

Section: The Development Results Of Muc Control Automation Tasks 1 Dmentioning

confidence: 99%

Control Automation of Maritime Unmanned Complex With a Group of Autonomous Underwater Vehicles

Blintsov

Aloba

2019

EUREKA: Physics and Engineering

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It is expedient to perform underwater search operations on large water areas using a group of autonomous self-propelled underwater vehicles. However, with a large distance to the search areas, the sea transition (from one point to the other) of the underwater vehicles requires high energy costs. This leads to the necessity to use heavy-duty underwater vehicles, which determines the high cost of the search operation. The transport of underwater vehicles is proposed to be carried out with an unmanned surface vessel, equipped with actuators for the automatic release of a group of vehicles under water and receiving on board after the end of the underwater mission. The maritime unmanned complex consisting of an unmanned surface vessel and a group of autonomous underwater vehicles on its board forms a new type of marine robotics, the complete automation of which is an actual scientific and technical task. For its implementation, the underlying (basic) automation technology of the marine search underwater mission has been developed as the theoretical basis for the development of the generalized structure of the complex automatic control system. Ten implementation stages of the underlying technology are formulated and the analysis of their automation features with the use of modern methods in the field of marine robotics is performed. Automation of the underlying technology stages involves the transfer of the vessel to a given water area, the automatic release (launch) of the group of underwater vehicles and their coordinated motion to the search area, the search operations and the return to the unmanned surface vessel, as well as the recovery of the vessel to the base. The generalized requirements for automatic control systems constituting the maritime unmanned complex at each stage of its functioning are provided. The spiral trajectory of waiting for the motion of the underwater vehicles at the group formation stages, for the search operation execution and after its completion, is proposed. For the spatial motion of the autonomous underwater vehicle as an agent of the group, the automatic control system was improved by introducing the blocks of the "Navigation Situation Model" and the "Navigation Threat Identifier, which make it impossible for emergency collision with the neighboring underwater vehicles of the group and disintegrate the group due to the data communication loss between them.

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Section: The Development Results Of Muc Control Automation Tasks 1 Dmentioning

confidence: 99%

Control Automation of Maritime Unmanned Complex With a Group of Autonomous Underwater Vehicles

Blintsov

Aloba

2019

EUREKA: Physics and Engineering

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“…Next, no difference in efficiency was found among the navigational methods, except for the ALN. In the ALN, at least one AUV must land on the seafloor, and the communication time is required to alternate the landmark; hence, the efficiency worsened (Matsuda et al, 2018).…”

Section: Performance Evaluation: Comparison With Conventional Methodsmentioning

confidence: 99%

“…AUVs need to estimate their own position and pose accurately to conduct the surveying. We have previously proposed the ALN in which AUVs alternately land on the seafloor to act as a positioning landmark and support positioning of the other AUVs (Matsuda et al, 2012(Matsuda et al, , 2018. The ALN has the drawback because it requires one AUV must keep stationary on the seafloor.…”

Section: Surveying Outlinementioning

confidence: 99%

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

Self Cite

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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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“…Matsuda et al [49] developed navigation methods based on parent-child relationships to coordinate multiple AUVs in autonomous underwater surveys. In another work, Matsuda et al [50] developed a navigation method allowing multiple AUVs to conduct extensive seafloor surveys using alternating marker-based navigation. To facilitate identification, we summarized the initial identification of the above research in Table 1.…”

Section: Related Workmentioning

confidence: 99%

“…Path planning navigation assisted by terrain information [43] Autonomous SVM Single range only beacon navigation [47] Autonomous DL Utilize Microelectromechanical-system (MEMS) and Inertia-measurement-unit (IMU) navigation [48] Autonomous RL Develop Teach and repeat method Machine-learning (ML) navigation [49] Autonomous RL Develop Parent child ML method navigation [50] Autonomous RL Develop Alternating landmark navigation the nonlinear uncertainty residue from the modified linear data model and will be estimated collectively in the next control design process.…”

Section: Researchmentioning

confidence: 99%

An Autonomous Underwater Vehicle Navigation Technique for Inspection and Data Acquisition in UWSNs

Wibisono,

Piran,

Song

et al. 2024

IEEE Access

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This article introduces an innovative approach to the navigation of autonomous underwater vehicles (AUVs) in inspection and data acquisition missions within underwater wireless sensor networks (UWSNs). We combine at least five underwater navigation techniques to accomplish this mission, adapted from related works. These five techniques are employed to address at least four main challenges identified in inspection and data acquisition missions in UWSNs involving the use of AUVs, namely: communication constraints, energy usage optimization, precise navigation, and effective data acquisition. Limited simulations conducted demonstrate the reliability of the proposed model. The model successfully navigates to the target point in 3D coordinates X Y Z, assuming the launch point as d0 (10 40 40), and reaches the q-goal target point (45 45 0) within 21 seconds, with the addition of uattractive and urepulsive (magnetic beacon attraction force and repulsion force as simulation of underwater current disturbance factor). Furthermore, in the inspection and data acquisition mission in UWSN simulated as node points (o) in pink, AUV (*) in blue effectively follows the predetermined points while acquiring data, as indicated by green lines (-) within just 5 seconds, achievable by increasing the value of α (angle of attack) of the target node to reduce delay time. The evaluation of the experimental simulations has raised issues and future research challenges, including the development of environmental simulation challenges that can closely resemble real conditions, the measurement of energy usage effectiveness to reach each target point, and the potential development of underwater recharging techniques. Furthermore, there is a need for advanced precise navigation and the advancement of effective data acquisition techniques.

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Alternating landmark navigation of multiple AUVs for wide seafloor survey: Field experiment and performance verification

Cited by 12 publications

References 35 publications

Control Automation of Maritime Unmanned Complex With a Group of Autonomous Underwater Vehicles

Control Automation of Maritime Unmanned Complex With a Group of Autonomous Underwater Vehicles

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

An Autonomous Underwater Vehicle Navigation Technique for Inspection and Data Acquisition in UWSNs

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