DocumentCode :
507993
Title :
Path Planning of AUV in Turbulent Ocean Environments Used Adapted Inertia-Weight PSO
Author :
Yang, Ge ; Zhang, Rubo
Author_Institution :
Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
Volume :
3
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
299
Lastpage :
302
Abstract :
This paper proposes an adapted inertia-weight particle swarm optimal algorithm (AIPSO) for path planning of an autonomous underwater vehicle in a sea field environment characterized by strong currents. The goal is to find a safe path that takes the vehicle from its starting location to a mission-specified destination, while minimizing the energy cost. The PSO algorithm used here introduced a self-adapted inertia weight factor to speed up the convergence to the global minimum. The method is proved to be effective in simulation experiments. The proposed algorithm can make AUV travel longer and save more energy comparing to tradition path planning methods.
Keywords :
particle swarm optimisation; path planning; remotely operated vehicles; self-adjusting systems; underwater vehicles; AUV; adapted inertia-weight particle swarm optimal algorithm; autonomous underwater vehicle; path planning; sea field environment; self-adapted inertia weight factor; turbulent ocean environments; Computer science; Costs; Educational institutions; Marine technology; Oceans; Path planning; Remotely operated vehicles; Sea measurements; Underwater vehicles; Virtual colonoscopy; AUV; adapted inertia-weight PSO; current; path planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.355
Filename :
5364525
Link To Document :
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