A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint Guidance
It is a challengeable task to plan multi-objective optimization paths for autonomous underwater vehicles (AUVs) in an unknown environments, which involves reducing travel time, shortening path length, keeping navigation safety, and smoothing trajectory. To address the above challenges, a real-time p...
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doaj-350ec4968f3a451e8fe5d81c1707a1b12020-11-24T21:22:39ZengMDPI AGSensors1424-82202018-12-011912010.3390/s19010020s19010020A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint GuidanceZheping Yan0Jiyun Li1Yi Wu2Gengshi Zhang3Marine Assembly and Automatic Technology Institute, College of Automation, Harbin Engineering University, Harbin 150001, ChinaMarine Assembly and Automatic Technology Institute, College of Automation, Harbin Engineering University, Harbin 150001, ChinaMarine Assembly and Automatic Technology Institute, College of Automation, Harbin Engineering University, Harbin 150001, ChinaMarine Assembly and Automatic Technology Institute, College of Automation, Harbin Engineering University, Harbin 150001, ChinaIt is a challengeable task to plan multi-objective optimization paths for autonomous underwater vehicles (AUVs) in an unknown environments, which involves reducing travel time, shortening path length, keeping navigation safety, and smoothing trajectory. To address the above challenges, a real-time path planning approach combining particle swarm optimization and waypoint guidance is proposed for AUV in unknown oceanic environments in this paper. In this algorithm, a multi-beam forward looking sonar (FLS) is utilized to detect obstacles and the output data of FLS are used to produce those obstacles’ outlines (polygons). Particle swarm optimization is used to search for appropriate temporary waypoints, in which the optimization parameters of path planning are taken into account. Subsequently, an optimal path is automatically generated under the guidance of the destination and these temporary waypoints. Finally, three algorithms, including artificial potential field and genic algorithm, are adopted in the simulation experiments. The simulation results show that the proposed algorithm can generate the optimal paths compared with the other two algorithms.http://www.mdpi.com/1424-8220/19/1/20path planningparticle swarm optimizationwaypoint guidanceautonomous underwater vehicleforward looking sonar |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zheping Yan Jiyun Li Yi Wu Gengshi Zhang |
spellingShingle |
Zheping Yan Jiyun Li Yi Wu Gengshi Zhang A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint Guidance Sensors path planning particle swarm optimization waypoint guidance autonomous underwater vehicle forward looking sonar |
author_facet |
Zheping Yan Jiyun Li Yi Wu Gengshi Zhang |
author_sort |
Zheping Yan |
title |
A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint Guidance |
title_short |
A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint Guidance |
title_full |
A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint Guidance |
title_fullStr |
A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint Guidance |
title_full_unstemmed |
A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint Guidance |
title_sort |
real-time path planning algorithm for auv in unknown underwater environment based on combining pso and waypoint guidance |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2018-12-01 |
description |
It is a challengeable task to plan multi-objective optimization paths for autonomous underwater vehicles (AUVs) in an unknown environments, which involves reducing travel time, shortening path length, keeping navigation safety, and smoothing trajectory. To address the above challenges, a real-time path planning approach combining particle swarm optimization and waypoint guidance is proposed for AUV in unknown oceanic environments in this paper. In this algorithm, a multi-beam forward looking sonar (FLS) is utilized to detect obstacles and the output data of FLS are used to produce those obstacles’ outlines (polygons). Particle swarm optimization is used to search for appropriate temporary waypoints, in which the optimization parameters of path planning are taken into account. Subsequently, an optimal path is automatically generated under the guidance of the destination and these temporary waypoints. Finally, three algorithms, including artificial potential field and genic algorithm, are adopted in the simulation experiments. The simulation results show that the proposed algorithm can generate the optimal paths compared with the other two algorithms. |
topic |
path planning particle swarm optimization waypoint guidance autonomous underwater vehicle forward looking sonar |
url |
http://www.mdpi.com/1424-8220/19/1/20 |
work_keys_str_mv |
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