A leader-follower algorithm for multiple AUV formations

Edwards, Dean B.; Bean, Thomas; Odell, D.L.; Anderson, Michael J.

doi:10.1109/auv.2004.1431191

Cited by 115 publications

(43 citation statements)

References 6 publications

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“…Cost reduction can be considerable as followers are generally only concerned with their position relative to the leader, requiring less complex hardware. A leader vehicle may transmit concurrent coordinates to each follower or remain independent, and certain followers can be suitably equipped to replace leader vehicles for system robustness in the case of leader failure [14].…”

Section: Background and Overviewmentioning

confidence: 99%

Underwater surveying and mapping using rotational potential fields for multiple autonomous vehicles

McIntyre

Naeem

Ali

et al. 2016

2016 IEEE International Conference on Underwater System Technology: Theory and Applications (USYS)

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General rights Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Abstract-This paper presents a new technique for exploration and mapping/surveying of underwater infrastructure and/or objects of interest, using multiple autonomous underwater vehicles (AUVs). The proposed method employs rotational potential fields, and extends them for use on multiple vehicles within a three dimensional environment. An inter-vehicle fluid formation is maintained throughout, free of angular constraints (or the need of a virtual vehicle). When an object of interest is approached, the formation is split and follows a smooth trajectory around opposite sides of its boundary. To fully utilise the potential of rotational fields, a unique local 2D-plane is created around every object within the 3D environment, which is employed for boundary coverage. Traditional artificial potential fields are used to guide vehicles towards each object in turn (and maintain the fluid formation), while rotational fields are employed within the local 2D-plane providing a smooth trajectory around opposing sides of every object. Simulation results show the method to be effective, providing a more stable trajectory. Comparison with the standard technique shows that the formation is maintained throughout and overall journey time is significantly reduced using this method.

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Section: Background and Overviewmentioning

confidence: 99%

Underwater surveying and mapping using rotational potential fields for multiple autonomous vehicles

McIntyre

Naeem

Ali

et al. 2016

2016 IEEE International Conference on Underwater System Technology: Theory and Applications (USYS)

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“…Recalling the definition of the distance (6) and the definitions (8), (14), and (19), it is easy to show that for a robot with m vertices moving in an environment populated by polygonal obstacles with n vertices, the complexity of the distance computation is O(3 · m · n · 6) where 3 accounts for the three subproblems to be solved to determine the distance and 6 is the number of candidate shortest paths providing the value of the distance function.…”

Section: Case 2-amentioning

confidence: 99%

Shortest Paths to Obstacles for a Polygonal Dubins Car

Giordano

Vendittelli

2009

IEEE Trans. Robot.

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Abstract-In this paper, we characterize the time-optimal trajectories leading a Dubins car in collision with the obstacles in its workspace. Due to the constant velocity constraint characterizing the Dubins car model, these trajectories form a sufficient set of shortest paths between any robot configuration and the obstacles in the environment. Based on these paths, we define and give the algorithm for computing a distance function that takes into account the nonholonomic constraints and captures the nonsymmetric nature of the system. The developments presented here assume that the obstacles and the robot are polygons although the methodology can be applied to different shapes.

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“…AUVs are capable of a wide range of applications, such as pipeline inspection [1,2], underwater search and rescue, mine-sweeping [3], and oceanographic exploration [4]. The tasks of current AUVs are relatively single, and in the future, AUVs will be able to perform a variety of tasks.…”

Section: Introductionmentioning

confidence: 99%

Layout Optimization of Two Autonomous Underwater Vehicles for Drag Reduction with a Combined CFD and Neural Network Method

et al. 2017

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This paper presents an optimization method for the design of the layout of an autonomous underwater vehicles (AUV) fleet to minimize the drag force. The layout of the AUV fleet is defined by two nondimensional parameters. Firstly, three-dimensional computational fluid dynamics (CFD) simulations are performed on the fleets with different layout parameters and detailed information on the hydrodynamic forces and flow structures around the AUVs is obtained. Then, based on the CFD data, a backpropagation neural network (BPNN) method is used to describe the relationship between the layout parameters and the drag of the fleet. Finally, a genetic algorithm (GA) is chosen to obtain the optimal layout parameters which correspond to the minimum drag. The optimization results show that (1) the total drag of the AUV fleet can be reduced by 12% when the follower AUV is located directly behind the leader AUV and (2) the drag of the follower AUV can be reduced by 66% when it is by the side of the leader AUV.

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A leader-follower algorithm for multiple AUV formations

Cited by 115 publications

References 6 publications

Underwater surveying and mapping using rotational potential fields for multiple autonomous vehicles

Underwater surveying and mapping using rotational potential fields for multiple autonomous vehicles

Shortest Paths to Obstacles for a Polygonal Dubins Car

Layout Optimization of Two Autonomous Underwater Vehicles for Drag Reduction with a Combined CFD and Neural Network Method

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