Techniques allowing for robust six degree-of-freedom vehicle trim are explored within the iterative rotorcraft sizing framework HYDRA. An optimization-based approach allows designers to find an acceptable local minimum solution of the trim problem for over-actuated vehicle configurations for which an infinite number of trim solutions exist. The performance and robustness of optimization algorithms suitable for the minimization of a nonlinear objective function subject to design variable bounds and equality constraints are compared using both a four degree-of-freedom and a six degree-of-freedom vehicle trim problems. The SciPy implementation of the sequential least squares programming algorithm was found to converge to a target objective function value up to 96% faster than a trust region algorithm for both problems. The six degree-of-freedom trim methodology using sequential least squares programming was then applied to the problem of sizing an omni-directional ocotocopter to be able to complete a mission taking into account multiple motor/rotor failures during the flight. © 2021, American Institute of Aeronautics and Astronautics Inc.. All rights reserved.