  This paper examines the question of finding feasible points to discrete-time
optimal control problems. The optimization problem of finding a feasible
trajectory is transcribed to an unconstrained optimal control problem. An
efficient algorithm, called FP-DDP, is proposed that solves the resulting
problem using Differential Dynamic Programming preserving feasibility with
respect to the system dynamics in every iteration. Notably, FP-DDP admits
global and rapid local convergence properties induced by a combination of a
Levenberg-Marquardt method and an Armijo-type line search. The efficiency of
FP-DDP is demonstrated against established methods such as Direct Multiple
Shooting, Direct Single Shooting, and state-of-the-art solvers.
