Future autonomous space missions will require autonomous rendezvous and docking operations. The servicing spacecraft must be able to determine the relative 6 degree-of-freedom (6 DOF) motion between the vehicle and the target spacecraft. One method to determine the relative 6 DOF position and attitude is with 3D ladar imaging. Ladar sensor systems can capture close-proximity range images of the target spacecraft, producing 3D point cloud data sets. These sequentially collected point-cloud data sets were then registered with one another using a point correspondence-less variant of the Iterative Closest Points (ICP) algorithm to determine the relative 6 DOF displacements. Simulation experiments were performed and indicated that the mean-squared error (MSE), angular error, mean, and standard deviations for position and orientation estimates did not vary as a function of position and attitude and meet most minimum angular and translational error requirements for rendezvous and dock. Furthermore, the computational times required by this algorithm were comparable to previously reported variants of the point-to-point and point-to-plane-based ICP variants for single iterations when the initialization was already performed.