Simultaneous topological map prediction and moving object trajectory prediction in unknown environments

To achieve fully autonomous mobile robot in unknown environment, a mapping and localization technique is required. Recently, in unknown dynamic environment, SLAMMOT (Simultaneous Localization and Mapping and Moving Object Tracking) is also attracted the extensive attention in this area. In this paper, we extended SLAMMOT problem to simultaneous map prediction and moving object trajectory prediction. The robot not only passively collects the data and executes SLAMMOT, but actively predicts the future scene. The recursive Bayesian formulation of SLAMMOT with scene prediction is also derived for real time operation. Preliminary results are also shown and validated the idea in this paper.