Planning and correction of the AUV coverage path in real time

Bagnitckii, Andrei; Inzartsev, Alexander; Pavin, Alexander

doi:10.1109/ut.2017.7890299

Cited by 12 publications

(4 citation statements)

References 22 publications

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“…The control input u i of the system can be defined based on consistency theory and BCM ( Bagnitckii et al, 2017 ):

where γ i is the feedback control gain coefficient greater than zero.

is the direction vector.…”

Section: Coverage Algorithm Designmentioning

confidence: 99%

“…Since then, a large number of researchers have extended the Voronoi diagram-based approach to solving more complex and practical coverage problems ( Stergiopoulos and Tzes, 2009 ; Stergiopoulos and Tzes, 2010 ; Sun et al, 2019 ). Bagnitckii et al (2017) used the AUV group to form a monitoring network and proposed a multi-objective optimal coverage control method for the AUV group based on a discrete information prediction method with known navigation trajectories. This method solves the problem of optimal coverage in the multi-target area of the AUV group, but its performance is insufficient in the face of unknown tracks and areas ( Chen et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Static Area Coverage Algorithm for Heterogeneous AUV Group Based on Biological Competition Mechanism

Guo

Chen

Zhao

et al. 2022

Front. Bioeng. Biotechnol.

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Static area coverage of the heterogeneous autonomous underwater vehicle (AUV) group is widely used in many fields. With the use of the centroidal Voronoi tessellation (CVT) algorithm, the coverage problem can be resolved. However, the CVT method, which is optimized with the location evaluation function, cannot consider the heterogeneity of AUVs when the group performs the static area coverage task and will cause a waste of resources. In this paper, considering different AUVs’ task requirements and detection capabilities comprehensively, we propose a coverage control optimization algorithm based on a biological competition mechanism (BCM). By using BCM, the task load of each AUV can be distributed consistently. In addition, we provide strict proof of the consistency of the algorithm based on the Lyapunov method. Simulation results demonstrate that with the proposed algorithm, the location distribution of the heterogeneous AUV group for area coverage is close to the balanced value, and the performance is better than the CVT algorithm for static area coverage.

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“…The control input u i of the system can be defined based on consistency theory and BCM ( Bagnitckii et al, 2017 ):

where γ i is the feedback control gain coefficient greater than zero.

is the direction vector.…”

Section: Coverage Algorithm Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Static Area Coverage Algorithm for Heterogeneous AUV Group Based on Biological Competition Mechanism

Guo

Chen

Zhao

et al. 2022

Front. Bioeng. Biotechnol.

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show abstract

“…In the case of side-scan sonar, in order to compensate the nadir gap in the center area of sonar image, the vehicle's inter-track distance is usually designed as half size of the sonar swath, while it can be taken as or near to the swath width in the case of multibeam echosounder. Here the details of how to determine the intertrack distance [17]- [20] is out of the scope of this paper, and we only consider the case where the inter-track distance is predefined and given as a constant value. On the other hand, in practice the search area is usually set by a series of way points on the map which further compose polygon(s).…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, in practice the search area is usually set by a series of way points on the map which further compose polygon(s). With the constant inter-track distance, the optimal coverage for this polygon search area usually means to design a path with minimum number of turns of the vehicles [20]. Consequently, the CPP problem considered in this paper can be formulated as follows: Given polygonal 2D search area, design a shortest way-points path with the minimum number of vehicle turns while restricting the vehicle's movement inside the polygon VOLUME 11, 2023 area.…”

Section: Introductionmentioning

confidence: 99%

Full Coverage of Confined Irregular Polygon Area for Marine Survey

Li,

Kang,

Kim

et al. 2023

IEEE Access

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This paper considers the coverage path planning (CPP) problem for marine surveys, where the survey vehicles' movements are confined in the irregular polygon search area. So this is a sort of milling problem [1] with the minimum number of turns in order for improvement of the acquired sonar image quality. For this purpose, this paper proposes a novel method called CbSPSA (calculation based shortest path search algorithm). Especially in the irregular corner area, this algorithm can easily calculate a kind of shortest path for its full coverage of this irregular area. For any given polygon, it can always be partitioned into convex polygon(s). In this paper, we only consider the case where these divided convex polygons are all connected one by one. In this case, the shortest path with minimum turns in each convex polygon can be easily searched by CbSPSA. And further by simply linking all of these pieces, the total coverage path for any given polygon area can be constructed. On the other hand, for a given polygon, usually there are several different cases of partition. Among the searched coverage paths for each of these different partitions, the final optimal coverage path is determined through a predefined criteria. Numerical simulation and analyses are carried out to demonstrate the effectiveness of the proposed method.INDEX TERMS Coverage path planning (CPP), marine surveys, lawn mowing, milling, convex polygon.

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A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

Panda

Subudhi

Pati

2020

Int. J. Autom. Comput.

148

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The underwater path planning problem deals with finding an optimal or sub-optimal route between an origin point and a termination point in marine environments. The underwater environment is still considered as a great challenge for the path planning of autonomous underwater vehicles (AUVs) because of its hostile and dynamic nature. The major constraints for path planning are limited data transmission capability, power and sensing technology available for underwater operations. The sea environment is subjected to a large set of challenging factors classified as atmospheric, coastal and gravitational. Based on whether the impact of these factors can be approximated or not, the underwater environment can be characterized as predictable and unpredictable respectively. The classical path planning algorithms based on artificial intelligence assume that environmental conditions are known apriori to the path planner. But the current path planning algorithms involve continual interaction with the environment considering the environment as dynamic and its effect cannot be predicted. Path planning is necessary for many applications involving AUVs. These are based upon planning safety routes with minimum energy cost and computation overheads. This review is intended to summarize various path planning strategies for AUVs on the basis of characterization of underwater environments as predictable and unpredictable. The algorithms employed in path planning of single AUV and multiple AUVs are reviewed in the light of predictable and unpredictable environments.

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Planning and correction of the AUV coverage path in real time

Cited by 12 publications

References 22 publications

A Static Area Coverage Algorithm for Heterogeneous AUV Group Based on Biological Competition Mechanism

A Static Area Coverage Algorithm for Heterogeneous AUV Group Based on Biological Competition Mechanism

Full Coverage of Confined Irregular Polygon Area for Marine Survey

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

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