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Abstract
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In this work, an improved algorithm for motion planning of autonomous underwater vehicles
(AUVs) is introduced based on the particle swarm optimization (PSO) algorithm and the optimal
control strategy. According to this algorithm, the spline population is replaced with a quadratic
polynomial to reduce the objective function. In addition, by using the line-distance-based path
regeneration, the nonholonomic boundary conditions are satisfied accurately and prevent
collision of underwater vehicles with other objects. Further, by employing a combination of the
coefficient decrement method and final angle-based calibration, a better optimized path is
achieved. The environment in which the vehicle operates is a large region of the Persian Gulf
with real predicted currents. The results show that by using a polynomial instead of a spline,
the path planning efficiency increases. In addition, by using the coefficient decrement method
and final angle-based calibration, the energy used for vehicle motion has been reduced
significantly.
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