Hui Sheng Lim1,*, Christopher K. H. Chin1, Shuhong Chai1, Neil Bose1,2
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 33-50, 2020, DOI:10.32604/cmes.2020.011648
Abstract This paper presents an online AUV (autonomous underwater vehicle)
path planner that employs path replanning approach and the SDEQPSO (selective
differential evolution-hybridized quantum-behaved particle swarm optimization)
algorithm to optimize an AUV mission conducted in an unknown, dynamic and
cluttered ocean environment. The proposed path replanner considered the effect
of ocean currents in path optimization to generate a Pareto-optimal path that
guides the AUV to its target within minimum time. The optimization was based
on the onboard sensor data measured from the environment, which consists of a
priori unknown dynamic obstacles and spatiotemporal currents. Different sensor
arrangements for the forward-looking sonar… More >
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