Conference Paper

Rao-Blackwellized Particle Filtering for Mapping Dynamic Environments

Sibley Sch. of Mech. & Aerosp. Eng., Cornell Univ., Ithaca, NY
DOI: 10.1109/ROBOT.2007.364071 Conference: Robotics and Automation, 2007 IEEE International Conference on
Source: IEEE Xplore

ABSTRACT A general method for mapping dynamic environments using a Rao-Blackwellized particle filter is presented. The algorithm rigorously addresses both data association and target tracking in a single unified estimator. The algorithm relies on a Bayesian factorization to separate the posterior into: 1) a data association problem solved via particle filter; and 2) a tracking problem with known data associations solved by Kalman filters developed specifically for the ground robot environment. The algorithm is demonstrated in simulation and validated in the real world with laser range data, showing its practical applicability in simultaneously resolving data association ambiguities and tracking moving objects.