The problem of controlling the safe transition of a multirotor vehicle between its release from a parachute to the moment it reaches steady state flight is analyzed. The problems of optimal trajectory, controller tuning, safety and stability to initial conditions are also studied. The proposed solution involves a two step process to find a safe controller. First, an optimal control problem is defined and then transcribed, using a direct collocation method, into a nonlinear programming problem. Second, the trajectory error for a subset of initial conditions is calculated, and the worst case is defined as the overall cost. This emerging Min-Max problem is then solved using particle swarm optimization to obtain the best set of controller gains. In order to evaluate performance, a cost function based on margins between the vehicle’s state and their respective maximum allowable values was defined. Monte Carlo simulations were ran over the space of possible initial conditions. The combination of optimal trajectory and particle swarm derived controller gains results in an average state cost reduction of 23% when compared to a near-hover controller derived using Ziegler–Nichols method.