  We propose AstroSLAM, a standalone vision-based solution for autonomous
online navigation around an unknown target small celestial body. AstroSLAM is
predicated on the formulation of the SLAM problem as an incrementally growing
factor graph, facilitated by the use of the GTSAM library and the iSAM2 engine.
By combining sensor fusion with orbital motion priors, we achieve improved
performance over a baseline SLAM solution. We incorporate orbital motion
constraints into the factor graph by devising a novel relative dynamics factor,
which links the relative pose of the spacecraft to the problem of predicting
trajectories stemming from the motion of the spacecraft in the vicinity of the
small body. We demonstrate the excellent performance of AstroSLAM using both
real legacy mission imagery and trajectory data courtesy of NASA's Planetary
Data System, as well as real in-lab imagery data generated on a 3
degree-of-freedom spacecraft simulator test-bed.
