Machine-learned model architecture for predicting future object trajectory

Predicting a future trajectory of an object may comprise using a machine-learned model architecture to iteratively predict a series of predicted poses (positions and orientations) of the object over time. The machine-learned model may condition these predictions on a lane orientation of nearest target pose to a predicted pose or last predicted pose of the object.