A Path Planning Algorithm Based on Parallel Particle Swarm Optimization

2014 ◽  
pp. 82-90
Author(s):  
Weitao Dang ◽  
Kai Xu ◽  
Quanjun Yin ◽  
Qixin Zhang
Keyword(s):  
Particle Swarm Optimization ◽  
Path Planning ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Planning Algorithm ◽  
Parallel Particle Swarm Optimization ◽  
Path Planning Algorithm

scholarly journals A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint Guidance

Sensors ◽  
2018 ◽  
Vol 19 (1) ◽  
pp. 20 ◽  
Author(s):  
Zheping Yan ◽  
Jiyun Li ◽  
Yi Wu ◽  
Gengshi Zhang
Keyword(s):  
Particle Swarm Optimization ◽  
Path Planning ◽  
Real Time ◽  
Autonomous Underwater Vehicles ◽  
Optimal Path ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Time Path ◽  
Optimization Parameters ◽  
Planning Algorithm

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.

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