Data Association for FastSLAM in Unknown Environments

The data association issues of FastSLAM (Factored Solution to SLAM) algorithm in unknown environments were discussed. In normal FastSLAM,it always hypothesizes that the data association is certain. But in real world,the data association is uncertain. An new approach which united per-particle maximum likelihood data association and negative information technology was adopted to handle the uncertainty of data association for FastSLAM. Simulination experimental results show that the new data association method for FastSLAM improves robot performances of localization and mapping in unknown environments.