Path Planning for Autonomous Underwater Vehicles

Clment Petres(Heriot-Watt University), Yan Pailhas(Heriot-Watt University), Pedro Patrón(Heriot-Watt University), Yvan Pétillot(Heriot-Watt University), Jonathan Evans(Heriot-Watt University), David M. Lane(Heriot-Watt University)
IEEE Transactions on Robotics
April 1, 2007
Cited by 430

Abstract

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Efficient path-planning algorithms are a crucial issue for modern autonomous underwater vehicles. Classical path-planning algorithms in artificial intelligence are not designed to deal with wide continuous environments prone to currents. We present a novel Fast Marching (FM)-based approach to address the following issues. First, we develop an algorithm we call FM* to efficiently extract a 2-D continuous path from a discrete representation of the environment. Second, we take underwater currents into account thanks to an anisotropic extension of the original FM algorithm. Third, the vehicle turning radius is introduced as a constraint on the optimal path curvature for both isotropic and anisotropic media. Finally, a multiresolution method is introduced to speed up the overall path-planning process. </para>


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