Journal ArticleDOI
Evolutionary path planning for autonomous underwater vehicles in a variable ocean
TLDR
A genetic algorithm for path planning of an autonomous underwater vehicle in an ocean environment characterized by strong currents and enhanced space-time variability is proposed, suitable for situations in which the vehicle has to operate energy-exhaustive missions.Abstract:
This paper proposes a genetic algorithm (GA) for path planning of an autonomous underwater vehicle in an ocean environment characterized by strong currents and enhanced space-time variability. The goal is to find a safe path that takes the vehicle from its starting location to a mission-specified destination, minimizing the energy cost. The GA includes novel genetic operators that ensure the convergence to the global minimum even in cases where the structure (in space and time) of the current field implies the existence of different local minima. The performance of these operators is discussed. The proposed algorithm is suitable for situations in which the vehicle has to operate energy-exhaustive missions.read more
Citations
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Journal ArticleDOI
Path Planning for Autonomous Underwater Vehicles
TL;DR: This work develops an algorithm, called FM*, to efficiently extract a 2-D continuous path from a discrete representation of the environment and takes underwater currents into account thanks to an anisotropic extension of the original FM algorithm.
Proceedings ArticleDOI
Path Planning of Autonomous Underwater Vehicles in Current Fields with Complex Spatial Variability: an A* Approach
TL;DR: Results indicate that substantial energy savings of planned paths compared to straight line trajectories are obtained when the current intensity of the eddy structures and the vehicle speed are comparable.
Journal ArticleDOI
Dynamic Task Assignment and Path Planning of Multi-AUV System Based on an Improved Self-Organizing Map and Velocity Synthesis Method in Three-Dimensional Underwater Workspace
TL;DR: An integrated multiple autonomous underwater vehicle (AUV) dynamic task assignment and path planning algorithm is proposed by combing the improved self-organizing map (SOM) neural network and a novel velocity synthesis approach for a 3-D underwater workspace with a variable ocean current.
Journal ArticleDOI
A survey on path planning for persistent autonomy of autonomous underwater vehicles
TL;DR: The main objective of this paper is to present a comprehensive survey of shape and properties of the path and optimization techniques for path planning, which have been classified into different classes and their assumptions and drawbacks have been discussed.
Journal ArticleDOI
A constrained A* approach towards optimal path planning for an unmanned surface vehicle in a maritime environment containing dynamic obstacles and ocean currents
TL;DR: Even after embargo period expires, authors' right to distribute as green open access is conditional on the green openAccess version including a DOI link, and on thegreen open access version being distributed under the Creative Commons CC-BY-NC-ND licence.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Book
Robot Motion Planning
TL;DR: This chapter discusses the configuration space of a Rigid Object, the challenges of dealing with uncertainty, and potential field methods for solving these problems.