Consistent integration and propagation of disparate sensor observations

We present a theory and methodology for integrating and propagating geometric sensor observations. The integration policy takes any number of disparate, partial and uncertain observations and optimaly combines them into a minimum-risk best estimate consensus view of the state of the environment. These consensus observations are considered to be integrated into a geometric model of the world. A methodology is developed that propagates new observations through this world model, maintaining consistency amongst objects and making maximum use of sensor information.