For learning object models, we made initial scan alignment more robust by adapting the point-pair feature object detection and pose estimation method of Papazov et al. (ACCV 2010). We only allow transformations that are close to the expected ones in the RANSAC step.

For active object perception, we extended the simulation to include the complete experiment setup, adapted the object recognition method to identify regions of interest, and integrated the planning of the next best view (NBV).