  We propose an online spatiotemporal articulation model estimation framework
that estimates both articulated structure as well as a temporal prediction
model solely using passive observations. The resulting model can predict future
mo- tions of an articulated object with high confidence because of the spatial
and temporal structure. We demonstrate the effectiveness of the predictive
model by incorporating it within a standard simultaneous localization and
mapping (SLAM) pipeline for mapping and robot localization in previously
unexplored dynamic environments. Our method is able to localize the robot and
map a dynamic scene by explaining the observed motion in the world. We
demonstrate the effectiveness of the proposed framework for both simulated and
real-world dynamic environments.
