  In this study, a single autonomous underwater vehicle (AUV) aims to
rendezvous with a submerged leader recovery vehicle through a cluttered and
variable operating field. The rendezvous problem is transformed into a
nonlinear optimal control problem (NOCP) and then numerical solutions are
provided. A penalty function method is utilized to combine the boundary
conditions, vehicular and environmental constraints with the performance index
that is final rendezvous time.Four evolutionary based path planning methods
namely particle swarm optimization (PSO), biogeography-based optimization
(BBO), differential evolution (DE) and Firefly algorithm (FA) are employed to
establish a reactive planner module and provide a numerical solution for the
proposed NOCP. The objective is to synthesize and analysis the performance and
capability of the mentioned methods for guiding an AUV from loitering point
toward the rendezvous place through a comprehensive simulation study.The
proposed planner module entails a heuristic for refining the path considering
situational awareness of underlying environment, encompassing static and
dynamic obstacles overwhelmed in spatiotemporal current vectors.This leads to
accommodate the unforeseen changes in the operating field like emergence of
unpredicted obstacles or variability of current vector filed and turbulent
regions. The simulation results demonstrate the inherent robustness and
significant efficiency of the proposed planner in enhancement of the vehicle's
autonomy in terms of using current force, coping undesired current disturbance
for the desired rendezvous purpose. Advantages and shortcoming of all utilized
methods are also presented based on the obtained results.
