Efficient multi-AUV cooperation using semantic knowledge representation for underwater archaeology missions

Tsiogkas, Nikolaos; Papadimitriou, Georgios; Saigol, Zeyn; Lane, David M.

doi:10.1109/oceans.2014.7003085

Cited by 26 publications

(15 citation statements)

References 13 publications

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“…The issue of group control of autonomous vehicles-robots has been highlighted over the past 10 years [4,5]. The works associated with the use of Multi-Agent Systems (MAS) in maritime environmental and archaeological researches are of particular relevance [6,7].…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…The NTI threat Identification block evaluates the degree of collision threat with the AUV-neighbors and/or the threat of losing contact with the AUVs group in the event of a horizontal maneuver according to dependencies (4), (5), and also calculates a forecast of the group motion dynamics identified by AUV-neighbors. The NTI block contains a module for calculating the derivative distances of identified targets (Calculus of Derivative, CD) and navigational threats calculator (Calculus of Navigation Threat, CNT), which is proposed to be built on the basis of fuzzy logic [23].…”

Section: Synthesis Of Acs Of Individual Auv Spatial Motion As a Grmentioning

confidence: 99%

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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: Literature Review and Problem Statementmentioning

confidence: 99%

Section: Synthesis Of Acs Of Individual Auv Spatial Motion As a Grmentioning

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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“…An inherent goal of the ARROWS project is to achieve persistent autonomy of an underwater multi-vehicle system (Tsiogkas et al (2014)). There is one main problem that must be solved in order to achieve this: how to efficiently share information (of the world and mission) between platforms in the marine domain.…”

Section: High Level Control Systemmentioning

confidence: 99%

The ARROWS project: adapting and developing robotics technologies for underwater archaeology

et al. 2015

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ARchaeological RObot systems for the World's Seas (ARROWS) EU Project proposes to adapt and develop low-cost Autonomous Underwater Vehicle (AUV) technologies to significantly reduce the cost of archaeological operations, covering the full extent of archaeological campaign. ARROWS methodology is to identify the archaeologists requirements in all phases of the campaign and to propose related technological solutions. Starting from the necessities identified by archaeological project partners in collaboration with the Archaeology Advisory Group, a board composed of European archaeologists from outside ARROWS, the aim is the development of a heterogeneous team of cooperating AUVs capable of comply with a complete archaeological autonomous mission. Three new different AUVs have been designed in the framework of the project according to the archaeologists' indications: MARTA, characterized by a strong hardware modularity for ease of payload and propulsion systems configuration change; U-CAT, a turtle inspired bio-mimetic robot devoted to shipwreck penetration and A Size AUV, a vehicle of small dimensions and weight easily deployable even by a single person. These three vehicles will cooperate within the project with AUVs already owned by ARROWS partners exploiting a distributed high-level control software based on the World Model Service (WMS), a storage system for the environment knowledge, updated in real-time through online payload data process, in the form of an ontology. The project includes also the development of a cleaning tool for well-known artifacts maintenance operations. The paper presents the current stage of the project that will lead to overall system final demonstrations, during Summer 2015, in two different scenarios, Sicily (Italy) and Baltic Sea (Estonia).

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“…This approach is using the k-Means machine learning algorithm to cluster tasks and then allocates them to robots. The work presented in the current paper builds upon [12] where a centralised experimental evaluation of the k-Means allocation was presented.…”

Section: Related Workmentioning

confidence: 99%

Distributed multi-AUV cooperation methods for underwater archaeology

Tsiogkas

Saigol

Lane

2015

OCEANS 2015 - Genova

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Abstract-Autonomous Underwater Vehicles (AUVs) are a useful tool for science and industry. They significantly reduce the risk to humans in operations in hazardous and high cost situations. The use of multiple AUVs can enhance the operational capabilities by introducing specialisation of AUV capabilities and parallelising task execution. The coordination of the multi-AUV team requires communication among its members. Underwater communications are low bandwidth, high latency and error prone. This paper studies different task allocation strategies for an underwater archaeological inspection scenario under communication constraints. Three different distributed methods are implemented and compared in simulation. The first is a greedy allocation method used as a baseline for comparison. The second is a k-Means based formulation aiming to balance the load among the robots. The third is the linear programming formulation of the multiple travelling salesmen problem. Results are analysed in the scope of mission completion time and the distance travelled by the robots. Results indicate that the k-Means method performs better when communication error rates are lower, while the mTSP method performs better when communication error rates are higher.

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Efficient multi-AUV cooperation using semantic knowledge representation for underwater archaeology missions

Cited by 26 publications

References 13 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

The ARROWS project: adapting and developing robotics technologies for underwater archaeology

Distributed multi-AUV cooperation methods for underwater archaeology

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