Multi-Robot Mapping

A new representation and algorithm for cooperative and persistent simultaneous localization and mapping (SLAM) using multiple robots is studied. Recent pose graph representations have proven very successful for single robot mapping and localization. Among these methods, iSAM (incremental smoothing and mapping) gives an exact incremental solution to the SLAM problem by solving a full nonlinear optimization problem in real-time. We present a novel extension to iSAM to facilitate multi-robot mapping based on multiple pose graphs. The main contribution is a relative formulation of the relationship between multiple pose graphs. Formulation avoids the initialization problem and leads to an efficient solution when compared to a completely global solution.