27. The autonomous vehicle of claim 26 , wherein estimating the rotation comprises: generating hypotheses for the rotation, each of the hypotheses identifying an estimated rotation; identifying, from the hypotheses, low-noise hypotheses at least in part by identifying a mode of the estimated rotations and a subset of the hypotheses within a threshold amount of the mode, the subset of the hypotheses being the low-noise hypotheses; and averaging estimated rotations of the low-noise hypotheses to obtain the rotation for the first object.
26. An autonomous vehicle comprising: at least one camera; at least one processor; and at least one storage medium having encoded thereon executable instructions that, when executed by the at least one processor, cause the at least one processor to carry out a method for guidance and navigation of the autonomous vehicle, the method comprising: processing a plurality of images captured by the at least one camera over a period of time to track a first object in an environment of the autonomous vehicle, wherein tracking the first object comprises estimating a relative pose of the first object between a first image and a second image of the plurality of images, wherein estimating the relative pose of the first object comprises: estimating a translation of the first object between the first image and the second image based at least in part on the first image and the second image, and separately from estimating the translation, estimating a rotation of the first object between the first image and the second image based at least in part on the first image and the second image.