Greedy Mechanism Based Particle Swarm Optimization for Path Planning Problem of an Unmanned Surface Vehicle

Recently, issues of climate change, environment abnormality, individual requirements, and national defense have caused extensive attention to the commercial, scientific, and military development of unmanned surface vehicles (USVs). In order to design high-quality routes for a multi-sensor integrated...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 19; no. 21; p. 4620
Main Authors: Xin, Junfeng, Zhong, Jiabao, Li, Shixin, Sheng, Jinlu, Cui, Ying
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 24.10.2019
MDPI
Subjects:
2-opt operation
Algorithms
Efficiency
Global positioning systems
GPS
greedy mechanism
Heuristic
Literature reviews
Methods
Optimization
particle swarm optimization
path planning problem
Planning
unmanned surface vehicle
greedy mechanism
path planning problem
unmanned surface vehicle
particle swarm optimization
2-opt operation
ISSN:1424-8220, 1424-8220
Online Access:Get full text
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Summary:Recently, issues of climate change, environment abnormality, individual requirements, and national defense have caused extensive attention to the commercial, scientific, and military development of unmanned surface vehicles (USVs). In order to design high-quality routes for a multi-sensor integrated USV, this work improves the conventional particle swarm optimization algorithm by introducing the greedy mechanism and the 2-opt operation, based on a combination strategy. First, a greedy black box is established for particle initialization, overcoming the randomness of the conventional method and excluding a great number of infeasible solutions. Then the greedy selection strategy and 2-opt operation are adopted together for local searches, to maintain population diversity and eliminate path crossovers. In addition, Monte-Carlo simulations of eight instances are conducted to compare the improved algorithm with other existing algorithms. The computation results indicate that the improved algorithm has the superior performance, with the shortest route and satisfactory robustness, although a fraction of computing efficiency becomes sacrificed. Moreover, the effectiveness and reliability of the improved method is also verified by its multi-sensor-based application to a USV model in real marine environments.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s19214620