Abstract
This article presents a comparison of different path-planning algorithms for autonomous underwater vehicles using terrain-aided navigation. Four different path-planning methods are discussed: the genetic algorithm, the A* algorithm, the rapidly exploring random tree* algorithm, and the ant colony algorithm. The goal of this article is to compare the four methods to determine how to obtain better positioning accuracy when using terrain-aided navigation as a means of navigation. Each algorithm combines terrain complexity to comprehensively consider the motion characteristics of the autonomous underwater vehicles, giving reachable path between the start and end points. Terrain-aided navigation overcomes the challenges of underwater domain, such as visual distortion and radio frequency signal attenuation, which make landmark-based localization infeasible. The path-planning algorithms improve the terrain-aided navigation positioning accuracy by considering terrain complexity. To evaluate the four algorithms, we designed simulation experiments that use real-word seabed bathymetry data. The results of autonomous underwater vehicle navigation by terrain-aided navigation in these four cases are obtained and analyzed.
Highlights
IntroductionAutonomous underwater vehicle (AUV) and its related technologies have developed rapidly, and autonomous underwater vehicle (AUV) has become an important tool for human exploration of the deep sea.[1,2] accurate underwater positioning and navigation methods still restrict the long-range underwater operations for AUVs. Global positioning system, inertial navigation system (INS),[3,4] ultrashort baseline (USBL),[5] long baseline (LBL)[6] acoustic positioning systems, and geophysical navigation, such as terrain-aided navigation (TAN)[7] and geomagnetic matching navigation, all provide options for improving navigational accuracy, with various levels of attainable precision
In recent decades, autonomous underwater vehicle (AUV) and its related technologies have developed rapidly, and AUV has become an important tool for human exploration of the deep sea.[1,2] accurate underwater positioning and navigation methods still restrict the long-range underwater operations for AUVs
inertial navigation system (INS) has high navigation accuracy with expensive auxiliary equipment such as attitude heading reference systems and Doppler velocity logs (DVL), INS navigation error is related to the total distance traveled, which means it could not suit for long-time underwater navigation without other
Summary
Autonomous underwater vehicle (AUV) and its related technologies have developed rapidly, and AUV has become an important tool for human exploration of the deep sea.[1,2] accurate underwater positioning and navigation methods still restrict the long-range underwater operations for AUVs. Global positioning system, inertial navigation system (INS),[3,4] ultrashort baseline (USBL),[5] long baseline (LBL)[6] acoustic positioning systems, and geophysical navigation, such as terrain-aided navigation (TAN)[7] and geomagnetic matching navigation, all provide options for improving navigational accuracy, with various levels of attainable precision. Geophysical navigation, especially TAN, has been one feasible method for AUV underwater navigation due to its bounded error and no requirement of auxiliary equipment
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