A dynamic 3D environmental model with real-time access functions for use in autonomous mobile robots

A model of the environment is a mandatory requirement for the autonomy of a mobile robot. In this paper, we present a framework for the prediction of expected sensor images on feature level, which is based on a-priori knowledge about the geometry of the environment. Our algorithm is capable to serve all distance and image measuring sensors typically found on mobile robots in real time. Fast prediction is achieved by using concepts from database technology and computer graphics. By incorporating differences between the expected and sensed image, the model can be adapted to changes and uncertainties in the environment. So the predicted features can be attributed with uncertainties to support and enhance the match process.