A new method for switching between structures consisting of equivalent discrete and flexible objects with different particle representation and object configuration, including different resolution levels (number of particles per object), is reported. The method is fully general since it does not require any extra code nor additional database elements for new systems. It is based on a Monte Carlo sampling of the configurational space for each object type of the target system. The sampling is controlled by a Metropolis acceptance criterion of movements (translations, rotations, and relative deformations of the object configuration) that uses the generalized distance between the sets of particles at both representations. For Gaussian distributed distances, such a minimization procedure is equivalent to an optimization of χ2 in a maximum likelihood method. This provides sound statistical support since the method leads to the most probable configuration of the system at each representation. The configurations obtained in this way are then used to create resolution exchange maps for each object type, which allows the extrapolation of the conversion to every object configuration throughout the whole system. As an example, the method is here tested with several molecular dynamics simulated systems (ionic liquids, cyclodextrins, cell-penetrating peptides, cyclic peptides, lipid bilayers, vesicles, heterogeneous organic molecules, DNA, and solvated proteins) for different resolution force fields (GROMOS, AMBER, OPLS, MARTINI) using GROMACS. In this context, the method can be applied to map structures described by any other pair of force fields, as well as to homogeneous and heterogeneous systems with many different molecules. The method is proved to be highly efficient since the time required for the mapping is practically independent of the number of molecules in the target system.