The routing problem of autonomous underwater vehicles in ocean currents

Yan, Weisheng; Bai, Xiaoshan; Peng, Xingguang; Zuo, Lei; Dai, Jiguo

doi:10.1109/oceans-taipei.2014.6964486

Cited by 10 publications

(13 citation statements)

References 11 publications

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“…In the scope of underwater operations, Yan et al [94] developed an integrated mission planning strategy to serve the AUVs' routing and tasking problem, while minimizing total energy cost in the presence of ocean currents was the main objective of the study. Iori and Ledesma [95] proposed a behavior-based controller coupled with waypoint tracking scheme for a double vehicle routing-task planning problem with multiple stacks, where the routing problem is modeled with a Double Traveling Salesman Problem with Multiple Stacks (DTSPMS) for a single-vehicle pickup-and-delivery problem.…”

Section: Autonomous Mission Planning and Management Systems For Swarmmentioning

confidence: 99%

Current advancements on autonomous mission planning and management systems: An AUV and UAV perspective

Atyabi

MahmoudZadeh

Nefti‐Meziani

2018

Annual Reviews in Control

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Advances in hardware technology have enabled more integration of sophisticated software, triggering progresses in development and employment of Unmanned Vehicles (UVs), and mitigating restraints for onboard intelligence. As a result, UVs can now take part in more complex mission where continuous transformation in environmental condition calls for higher level of situational responsiveness. This paper serves as an introduction to UVs mission planning and management systems aiming to highlight some of the recent developments in the field of autonomous underwater and aerial vehicles in addition to stressing some possible future directions and discussing the learned lessons. A comprehensive survey over autonomy assessment of UVs, and different aspects of autonomy such as situation awareness, cognition, and decision-making has been provided in this study. The paper separately explains the humanoid and autonomous system's performance and highlights the role and impact of a human in UVs operations.

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Section: Autonomous Mission Planning and Management Systems For Swarmmentioning

confidence: 99%

Current advancements on autonomous mission planning and management systems: An AUV and UAV perspective

Atyabi

MahmoudZadeh

Nefti‐Meziani

2018

Annual Reviews in Control

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“…Therefore, during the last few years researchers have almost discarded these types of functions for RT path planning and have focused on similar approaches. For instance, those developed for underwater robots that account for ocean currents and obstacles by means of the definition of drift fields and the use of grid-based planning strategies ( [14,15]). Additionally, the optimal control theory is very popular for path planning in this context, particularly multi-population genetic algorithms or clustering-based algorithms to solve vehicle task assignments [16].…”

Section: Introductionmentioning

confidence: 99%

A Path Planning Algorithm for a Dynamic Environment Based on Proper Generalized Decomposition

et al. 2020

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A necessity in the design of a path planning algorithm is to account for the environment. If the movement of the mobile robot is through a dynamic environment, the algorithm needs to include the main constraint: real-time collision avoidance. This kind of problem has been studied by different researchers suggesting different techniques to solve the problem of how to design a trajectory of a mobile robot avoiding collisions with dynamic obstacles. One of these algorithms is the artificial potential field (APF), proposed by O. Khatib in 1986, where a set of an artificial potential field is generated to attract the mobile robot to the goal and to repel the obstacles. This is one of the best options to obtain the trajectory of a mobile robot in real-time (RT). However, the main disadvantage is the presence of deadlocks. The mobile robot can be trapped in one of the local minima. In 1988, J.F. Canny suggested an alternative solution using harmonic functions satisfying the Laplace partial differential equation. When this article appeared, it was nearly impossible to apply this algorithm to RT applications. Years later a novel technique called proper generalized decomposition (PGD) appeared to solve partial differential equations, including parameters, the main appeal being that the solution is obtained once in life, including all the possible parameters. Our previous work, published in 2018, was the first approach to study the possibility of applying the PGD to designing a path planning alternative to the algorithms that nowadays exist. The target of this work is to improve our first approach while including dynamic obstacles as extra parameters.

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“…In our previous work [15], the sensor delivery task assignment for multiple AUVs has been performed in temporally piece-wise constant ocean currents aiming at optimising the vehicles' total travel time. In addition, for vehicles operating in a time-varying drift field, a co-evolutionary multi-population genetic algorithm (GA) has been designed in [16] for multiple vehicles to deliver products to a set of target locations.…”

Section: Introductionmentioning

confidence: 99%

Distributed multi‐vehicle task assignment in a time‐invariant drift field with obstacles

Bai

Yan

Cao

et al. 2019

IET Control Theory & Applications

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The routing problem of autonomous underwater vehicles in ocean currents

Cited by 10 publications

References 11 publications

Current advancements on autonomous mission planning and management systems: An AUV and UAV perspective

Current advancements on autonomous mission planning and management systems: An AUV and UAV perspective

A Path Planning Algorithm for a Dynamic Environment Based on Proper Generalized Decomposition

Distributed multi‐vehicle task assignment in a time‐invariant drift field with obstacles

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