  In this paper, a real-time quasi-optimal trajectory planning scheme is
employed to guide an autonomous underwater vehicle (AUV) safely into a
funnel-shape stationary docking station. By taking advantage of the direct
method of calculus of variation and inverse dynamics optimization, the proposed
trajectory planner provides a computationally efficient framework for
autonomous underwater docking in a 3D cluttered undersea environment. Vehicular
constraints, such as constraints on AUV states and actuators; boundary
conditions, including initial and final vehicle poses; and environmental
constraints, for instance no-fly zones and current disturbances, are all
modelled and considered in the problem formulation. The performance of the
proposed planner algorithm is analyzed through simulation studies. To show the
reliability and robustness of the method in dealing with uncertainty, Monte
Carlo runs and statistical analysis are carried out. The results of the
simulations indicate that the proposed planner is well suited for real-time
implementation in a dynamic and uncertain environment.
